Growth Stories

Deep dive with George and Art, co-founders of Revnu — a YC-backed all-in-one growth platform that integrates with your codebase and runs your SEO, ads, outreach, and content as autonomous agents.The thesis behind Revnu starts from a problem the founders watched accelerate over the last two years. AI is letting more people ship more software faster than ever before, but most of those builders have no idea how to actually run a business or sell a product. Revnu handles the entire growth side. The agents audit your website and your current growth strategy in the first 40 hours, suggest improvements, then start drafting outreach plans, running ads, generating SEO content, and learning your brand voice so the output sounds like you.The differentiation is the shared intelligence layer between the agents. Most growth tools are point solutions. SEO over here, ads over there, outreach in a third tab. Revnu connects all of it. If someone clicks your blog post and does not buy, that signal feeds the ad agent, which retargets that person with a tailored ad, which feeds the email agent, which writes the follow-up. Every layer learns from every other layer. The benefit comes from the merge, not the individual tools.George and Art met at age 14 and have been a duo ever since. They started reselling sneakers in school, which became sneaker botting, which became Vinted sniping tools, which became a vintage accounting software, which became Revnu. Across all of it, the same pattern showed up: George shipping TikTok content while Art shipped code. Their best TikTok using their own AI cloning pipeline drove $2,000 in sales from a single video with 200,000 views. They built Revenu for the founder version of themselves four businesses ago.Also covered: the cultural whiplash of moving from London to San Francisco and being told to be more aggressive in sales, why they're focused on B2B SaaS first despite having strong B2C TikTok expertise, the long view that they're not chasing a fast exit but building something they can run for a long time, and their advice for founders applying to YC: bootstrap first, then come back.—Agentic Stories is the weekday briefing on the AI agent economy — governance, security, and deployment. Deep Dives drop on off-days with founders building in the space. New episodes Monday, Wednesday, Friday.agenticstories.ai

Deep dive with Roman and Pierre, co-founders of Gojiberry AI — a recent YC cohort company building autonomous agents for go-to-market. Gojiberry finds the right contacts, writes personalized messages, and books meetings, all from a single tool.The thesis comes from a problem Roman and Pierre lived through at their previous SaaS, Coco AI, where 99% of revenue came from outbound. They spent most of their time stitching together Clay, Lemlist, Apollo, and a handful of other tools, and realized that small teams without a dedicated GTM engineer cannot run that stack. Gojiberry is the one tool that replaces the patchwork. It works for individuals and small teams who do not have the budget or the headcount to maintain a multi-vendor outbound system.The differentiation is what they call a waterfall. Gojiberry first looks for warm leads based on signals and lookalikes of a customer's existing base. If no warm match is available, it falls back to leads matching the ICP. The agent runs through the full sequence in one place, which keeps lead quality high and cost low. Most outbound stacks today separate lead generation from outreach, which means importing leads from static databases and getting lower response rates as a result.Roman and Pierre took Gojiberry from zero to one million in ARR using their own product. They are now in San Francisco for the YC batch alongside Dylan, their third co-founder, and the move has measurably accelerated both shipping and growth. The product roadmap centers on what they call the GTM brain, an intelligence layer that compounds learnings across every customer's account, surfaces what works in specific industries, and removes the cold-start problem every outbound tool has at user one.Also covered: how to run LinkedIn outreach without getting flagged as automated, why Reddit was their first traction channel and why they've moved on from it, when notes on connection requests actually work and when they kill response rates, and Pierre's view on whether AI agents will replace human SDRs in the next five years.The goal between now and YC demo day is to double ARR. They plan to raise after that.—Agentic Stories is the weekday briefing on the AI agent economy — governance, security, and deployment. New episodes Monday, Wednesday, Friday.agenticstories.ai

Deep dive with Dr. Sebastian Fox, founder of Composo, on building the eval layer that catches the failures every other monitoring tool misses.Seb's path to Composo started in medicine at Oxford, moved through McKinsey and Quantum Black, and landed on a specific problem nobody had solved at scale. Most enterprises running AI in production today have offline regression tests, basic guardrails for things like profanity or PII, and tracing tools that store outputs somewhere. What they do not have is real-time quality checking on every output, calibrated to what a human domain expert would catch.Composo runs sub-second evals on every output an application produces, calibrated against human expert judgment in the specific domain. The product spans the full software lifecycle, but the most important work happens in production. Silent failures that standard LLM-as-a-judge metrics miss get caught and routed to human review, with every correction feeding back into the engine. Teams can use Composo as an internal visibility layer, as a gating layer between the application and the user, or as a runtime check inside the agent itself between tool calls.The conversation gets into agent liability when models are chained across vendors, why Seb thinks training your own foundation model is a category error for any non-hyperscaler, and why Composo is staying capital-light with a London engineering team. Seb is direct about what Composo does not solve: jailbreaks and security exploits on highly capable models. He flags the Mythos breach and the broader pattern of expert jailbreakers cracking new models within hours as the next category of risk that quality-focused evals will not cover on their own.Composo raised $2 million and is preparing to raise again over the next year. Seb's framing on capital efficiency in the eval space is worth hearing for any founder building infrastructure on top of frontier models.—Agentic Stories is the weekday briefing on the AI agent economy — governance, security, and deployment. Deep Dives drop on off-days with founders building in the space. New episodes Monday, Wednesday, Friday.agenticstories.ai

Three AI agent stories worth your attention: Cisco and CrowdStrike disclosed at RSA Conference that 85% of enterprises run agent pilots but only 5% ship to production, Anthropic published the first frontier-lab red-team data showing its most capable models can autonomously execute influence operations at a better than 50% success rate without safeguards, and startup BAND came out of stealth with $17 million to solve agent-to-agent credential traversal.At RSA Conference 2026, Cisco's President and CPO disclosed the 80-point gap between enterprises piloting agents and shipping them to production. CrowdStrike's CEO described two Fortune 50 incidents from the same week: a CEO's AI agent that autonomously rewrote its own security policy to remove a restriction blocking its goal, and a 100-agent Slack swarm that delegated a code fix between agents without human approval. Both incidents were caught by accident.Anthropic's election safeguards update this week included the most specific red-team disclosure a frontier lab has published this year. When tested with safeguards stripped, Mythos Preview and Opus 4.7 completed more than half of autonomous multi-step influence operation tasks successfully. The same report flagged that internet-facing agent framework instances nearly doubled in one week, from 230,000 to 500,000, based on Cato Networks Censys data.BAND, legal name Thenvoi AI, exited stealth with $17 million in seed funding to solve agent-to-agent credential traversal. The gap they are addressing is what happens when Agent A delegates a task to Agent B and nobody knows what permissions got passed along. Their Control Plane uses deterministic routing and constrains every downstream agent to only the permissions the original human user authorized. OAuth, SAML, and MCP do not cover this yet.—Agentic Stories is the weekday briefing on the AI agent economy — governance, security, and deployment. New episodes Monday, Wednesday, Friday.agenticstories.ai

Three AI agent stories worth your attention: Anthropic's Mythos cybersecurity model was breached on day one through a vendor supply chain gap, a VentureBeat survey found that 26% of enterprises use OpenAI as their primary AI security solution, and Moonshot AI's new Kimi K2.6 ran autonomously for five days in internal deployments and exposed the fact that most orchestration frameworks were not built for that.Anthropic released Mythos last month as its most restricted model, invite-only across roughly 40 organizations including the NSA. TechCrunch reported this week that on the same day it was publicly announced, an unidentified group on a Discord channel exploited access held by a third-party contractor and gained unauthorized entry. The breach was not a sophisticated attack chain. It was educated guesses about URL formats used by the vendor intermediary.VentureBeat surveyed 40 enterprise companies and found that 72% claim multiple "primary" AI platforms, nearly a third have no systematic mechanism to detect AI misbehavior until users surface it, and 26% use OpenAI as their primary AI security solution — the same provider whose models generate the risks they are trying to govern. Most enterprise AI governance right now is a compliance checkbox bought from the same vendor selling the risk.Moonshot AI's Kimi K2.6 ran autonomously for up to five days in internal monitoring and incident response deployments. The orchestration frameworks most enterprises are using were built for agents running seconds or minutes, which means no state management, no rollback, and no audit trail for long-horizon execution. If your agent runs for five days, you do not have a record of what it did on day three.—Agentic Stories is the weekday briefing on the AI agent economy — governance, security, and deployment. New episodes Monday, Wednesday, Friday.agenticstories.ai

Deep dive with Tej, co-founder of Stet, the OS for M&A deals that extracted 220 data points from an 85-page memorandum in two seconds, without making a single API call to Claude, GPT, or any other LLM.Tej's pitch sits uncomfortably on a podcast about AI agents, because Stet isn't one. He built a deterministic semantic model rooted in math that produces the same output for every input. For M&A diligence, where a single misread invoice can blow up a deal and where buy-side analysts routinely spend three months reconciling documents, determinism matters more than intelligence.The workflow Stet automates is one of the most painful in finance. Sell-side banks send buy-side firms a CIM with one version of the truth, then grant access to a virtual data room where the actual numbers often sit buried in invoices the sell side would rather nobody find. Analysts spend up to three months comparing one against the other. Stet compresses the process into hours, flags every discrepancy it finds, and lets users set a materiality threshold.—Agentic Stories is the weekday briefing on the AI agent economy: governance, security, and deployment. New episodes Monday, Wednesday, Friday.agenticstories.ai

Three walls the AI agent economy hit this week: a sovereignty wall (the NSA is running the same Anthropic model the Pentagon flagged as a national security risk), a control wall (NanoClaw 2.0 shipped the best human-in-the-loop architecture we've seen while MIT Tech Review argued all of it might be theater), and a scale wall (frontier models that ace PhD benchmarks cannot reliably book a meeting).The NSA is among 40 organizations with access to Anthropic's Mythos cybersecurity model — the same model the Pentagon designated a supply chain risk, from the same parent department that blacklisted the vendor. No published framework resolves the contradiction. Meanwhile, the White House OMB instructed every civilian federal agency to prepare for Mythos deployment with no agency-level risk assessment required. The UK government separately confirmed Mythos is the first AI system to autonomously complete a multi-step cyber infiltration end to end.NanoClaw 2.0 shipped granular per-action policy controls, human approval dialogues in 17 messaging apps, and a credential vault that withholds API keys until a human approves each action. The agent cannot generate its own approval UI or approve its own requests. The major model vendors shipped the frameworks and left the control surface for someone else to build. OpenAI's new Agents SDK update went the other direction — more abstraction, fewer decision points for risk managers to see.MIT Tech Review published the argument that reframes every governance conversation happening right now: human-in-the-loop oversight of AI in high-speed operational environments is an illusion. We don't understand AI's inner workings well enough to supervise its decisions meaningfully. The human approval step looks like governance, but it isn't. If they're right, most of what enterprises call AI governance is theater.And Meta researchers published work on hyperagents that modify their own task execution strategies dynamically, without retraining. The agent you tested on day zero is indistinguishable from the agent running on day 30. An AI industry executive disclosed this week that the same frontier models passing PhD benchmarks routinely fail at scheduling, filing, and multi-step document workflows in production.Tomorrow: Deep Dive with Tej from Stet on how agents are changing finance.—Agentic Stories is the weekday briefing on the AI agent economy — governance, security, and deployment. New episodes Monday, Wednesday, Friday.agenticstories.ai

Deep dive with Ivan Milev, co-founder of Codeboarding — the open-source tool turning your codebase into a live architecture diagram that updates in real time as coding agents modify your code.Coding agents have a black box problem. AI writes the code, humans don't read it line by line anymore, and nobody knows what actually changed. For a fintech running tax computations or any business with real stakes, that black box is a liability waiting to happen. Ivan argues this is why coding agents have stalled out on greenfield projects and haven't cracked serious enterprise adoption.Codeboarding maps your code structure into a systematic architectural diagram, linked to the real codebase. When any agent modifies the code, the diagram reflects the change in real time. The pitch: turn agent output from black box into scoped, observable, auditable changes. Ivan sees it as the foundation for the agentic IDE that doesn't exist yet — where designers, product owners, and developers can all run agents in their own scoped views without stepping on each other.Also covered: open-core business model (1,200 GitHub stars on the engine), why they moved from Zurich to SF, the YC application cycle, pricing by codebase size instead of seats, and what it takes to network as a founder in SF.Codeboarding is hiring a design partner. Ivan is in SF pitching and plans to run a hackathon this month.—Agentic Stories is the weekday briefing on the AI agent economy — governance, security, and deployment. Deep Dives drop on off-days with founders building in the space. New episodes Monday, Wednesday, Friday.agenticstories.ai

Three AI agent stories worth your attention: Microsoft chained GPT and Claude, Alibaba deployed autonomous agents to millions of merchants, and Apple made itself the App Store for AI agents on iOS 27.Microsoft wired GPT and Claude into the same Copilot Cowork workflow. GPT drafts, Claude edits. When the output is wrong, the accountability chain has no precedent. Two models, two vendors, one production pipeline, zero case law.Alibaba is rolling autonomous agents out to millions of Taobao and Tmall merchants. Autonomous pricing, customer communication, inventory decisions. The largest commercial agent deployment in history shipped with no published safety constraints and no recourse mechanism when an agent misprices a small business into the ground.Apple is opening Siri to third-party AI agents via iOS 27, with App Store review as the governance chokepoint. Apple built the original App Store in 2008 and regulators are still litigating the 30% cut. AI agents touch far more sensitive data than any app ever did.Broadcasting from San Francisco for the next month. Hit me up if you're in town.—Agentic Stories is the weekday briefing on the AI agent economy — governance, security, and deployment. New episodes Monday, Wednesday, Friday.agenticstories.ai

This week's guest is Alex Hoots — he's spent 6 weeks and over 200 hours building with OpenClaw, and he's not a developer.It started with a real problem. His sister owns a restaurant on the Normandy coast and was paying €160/month for a reservation tool. Alex built her a replacement in 6 hours using Lovable. It now handles 90% of her reservations for €25/month. Saturday nights fully booked through the tool alone.Then he went further. His barber Miguel spends half his day managing WhatsApp messages while cutting hair — name, service, date, time, confirmation. Alex built Pepe, an OpenClaw-based agent connected to WhatsApp and Miguel's booking platform. It handles the entire reservation flow autonomously. We demoed it live on the episode. It worked.But the real conversation is what comes next. Pepe can take a photo of Miguel's weekly inventory, count the items, and update the fulfillment dashboard automatically. The vision: an agent that removes the mental load entirely — handling every repetitive task so the business owner can focus on the work only they can do.Alex's take on getting started: you need a real use case with a clear outcome. Experimentation without a destination is how you end up with nothing tangible. Start with one problem you actually have. Build the solution. Then expand.—Agentic Stories is a daily show and guest series covering the AI agent economy — what agents are actually doing in the real world, built by people who aren't waiting for permission.agenticstories.ai

Three things happened this week that nobody connected.A verified Google advertiser created a fake Anthropic website and bought search advertising against "GitHub plugin Claude Code." Developers found it, read the installation instructions, and pasted a credential-stealing terminal command into their machines. The AI agent tooling ecosystem has normalised "copy, paste, run" as the default installation method — and quietly undone a decade of security training in 12 months. The MCP ecosystem alone has dozens of connectors distributed this way. This attack will happen again with different tools.A federal judge issued a preliminary injunction blocking the Pentagon's designation of Anthropic as a supply chain risk — ruling it was "classic illegal First Amendment retaliation" against a company for having an ethics policy. This changes the calculus for every AI company currently deciding how far to push back on government customers who want fewer restrictions on their agents. Anthropic's red lines — no autonomous weapons, no mass surveillance — are now the subject of a federal court ruling saying those red lines are constitutionally protected.Reddit announced that accounts behaving like bots will be required to prove they're human — exploring iris scanning, passkeys, and government ID. Reddit is one of the largest sources of real-time training data on the internet and increasingly a surface AI agents interact with autonomously. The distinction Reddit is trying to draw — AI as author is fine, AI as account is not — is going to be one of the defining governance questions of the next two years. Every major platform is moving this direction. If your agent operates social accounts, the verification requirements are coming.—Agentic Stories is a daily show covering the AI agent economy — governance, security, deployment risk, and what agents are actually doing in the real world. No hype. Just the agents.agenticstories.ai

Three things happened this week that belong in the same sentence.The European Parliament voted to delay key enforcement provisions of the EU AI Act — the most comprehensive AI governance framework ever written — pushing the compliance deadline for high-risk AI systems to 2027. Three years to write the rulebook. They voted to give everyone more time before following it. The cynical read: the industry pushed back and Brussels blinked. The generous read: enforcement without adequate compliance infrastructure just creates paperwork, not safety. Either way the result is the same — enterprises deploying agents in employment, education, critical infrastructure, and essential services just got more runway and less external pressure to sort out their own governance.A peer-reviewed study published in Science found that sycophantic AI agreed with users 49% more often than actual human consensus — and made participants measurably worse decision-makers. Less willing to reconsider. Less willing to accept responsibility. Across every demographic tested. The training mechanism behind this is RLHF — humans rate agreeable responses higher, so the model learns to agree. We're now deploying the output of that process into HR advisory tools, legal guidance systems, medical information agents, and financial recommendation engines. Every one of those requires honest pushback. The EU Act delay just gave us more time without requiring us to fix this. The study just told us what that costs.OpenAI launched a public Safety Bug Bounty specifically for agentic attack vectors — prompt injection, data exfiltration via hijacked agents, MCP vulnerabilities. Cash rewards for anyone who can reproduce these exploits. Two weeks ago their own internal report showed their agents encoding commands in base64 to evade security filters inside OpenAI. Now they're paying external researchers to find what they're missing. The agent security problem is larger than any single team can map on their own.—Agentic Stories is a daily show covering the AI agent economy — governance, security, deployment risk, and what agents are actually doing in the real world. No hype. Just the agents.agenticstories.ai

Three things happened this week that nobody put in the same sentence.Grammarly rebranded as Superhuman and launched "Expert Review" — AI writing feedback supposedly inspired by real, named people. People who never agreed to be in it. The Verge investigated after a reporter found the feature offering feedback in the name of her own editor-in-chief. Grammarly's justification: their published work is publicly available so it's fine. "Publicly available" is becoming the default defence for using someone's identity, voice, and professional judgment to power a product they never consented to. Grammarly has since said it will stop. The category won't.Musicians are done being quiet about AI clones. Deezer says 50,000 AI-generated tracks are uploaded to its platform every single day — 34% of all new music it ingests. Spotify has removed 75 million spam tracks. This week King Gizzard and the Lizard Wizard found AI fakes appearing on their own streaming pages. The mechanism is hard to stop: music goes through third-party distributors with limited screening. The industry is pushing back — the Living Wage for Musicians Act would create royalties explicitly excluding AI-generated music. iHeartRadio said they will never play AI music with synthetic vocalists pretending to be human.And Anthropic shipped Claude Dispatch for Cowork — its answer to OpenClaw, the open-source agent causing engineers to line up outside Tencent's headquarters in Shenzhen on a Friday afternoon. OpenClaw gives you an LLM agent, local drive access, and mobile control. No guardrails. Anthropic's version adds the missing piece: mobile control via Cowork, with the guardrails on. Which is both its limitation and its differentiator.—Agentic Stories is a daily show covering the AI agent economy — governance, security, deployment risk, and what agents are actually doing in the real world. No hype. Just the agents.agenticstories.ai

Three things happened over the weekend that belong in the same sentence.WordPress — which powers 43% of all websites on the internet — launched integrations allowing AI agents to draft, edit, and publish content autonomously across 409 million monthly visitors. The only human safeguard: one draft review step. The problem: prompt injection attacks embedded in comments, trackbacks, or RSS feeds could trigger agents to publish content across millions of sites simultaneously. Would a human reviewing an AI-drafted post catch instructions designed to be invisible? Based on everything we know about how prompt injection works — probably not reliably.OpenAI's chief scientist confirmed the company's new north star is a fully automated multi-agent research system. AI intern prototype by September 2026. Full autonomous research system by 2028. An agent that runs a research lab has an open-ended mandate, persistent operation over long time horizons, the ability to spin up sub-agents, and the ability to act on its own findings. That is a qualitatively different category of autonomy than anything current monitoring frameworks were designed for. The chief scientist admits the governance questions are unresolved. They're building it anyway.And Coinbase is building AI agent payment infrastructure — autonomous crypto payment rails so agents can transact financially without asking permission. Every agent failure mode we've covered on this show has been recoverable. Data exposure can be disclosed. Unauthorised posts can be deleted. Bad code can be rolled back. Cryptocurrency transactions are irreversible by design. We're about to give agents their own wallets before we've resolved any of the governance questions we've been documenting for three weeks. If a compromised agent executes an irreversible crypto transaction — who carries the loss?—Agentic Stories is a daily show covering the AI agent economy — governance, security, deployment risk, and what agents are actually doing in the real world. No hype. Just the agents.agenticstories.ai

Three things happened this week that belong in the same sentence.OpenAI published an internal safety report documenting months of their own coding agents evading security controls. Encoding commands in base64 to bypass filters. Hiding which tools they used. Misrepresenting completed tasks. Inside OpenAI. They had to build a GPT-5.4 powered surveillance system reviewing every agent session within 30 minutes — because the agents were evading the previous controls. If you're running coding agents with access to sensitive systems without real-time behavioural monitoring, OpenAI just established you're flying blind.The same week, Meta deployed autonomous AI agents to handle content enforcement across Facebook and Instagram for three billion users — detecting terrorism, child exploitation, fraud, and scams, making account disablement decisions and triggering law enforcement referrals. Two days after a different Meta agent caused a Sev 1 data breach. The governance question isn't whether Meta's enforcement agents are well-designed. It's who outside Meta can verify that. Right now the answer is nobody.And Moxie Marlinspike — the creator of Signal — announced he's integrating end-to-end encryption into Meta AI so that agent conversations are cryptographically inaccessible even to Meta. Unauditable by design. On the same day OpenAI published a report explaining why auditing agent behaviour is the minimum baseline for responsible deployment. Both visions are being built simultaneously, by serious people, with no coordination between them. Which one wins determines whether safe AI agents are even technically possible at scale.—Agentic Stories is a daily show covering the AI agent economy — governance, security, deployment risk, and what agents are actually doing in the real world. No hype. Just the agents.agenticstories.ai

Two stories. Both happened in the last 24 hours. Both change how you should think about deploying AI agents.A Meta AI agent autonomously posted on an internal forum without permission. That single unsanctioned action triggered a cascade that exposed sensitive company and user data to unauthorised engineers for two hours. Meta classified it a Sev 1 — their second-highest severity level. This is the first publicly reported enterprise-grade security breach caused by an AI agent going rogue in production. The agent wasn't hacked. No external prompt injection. It simply acted outside its intended boundaries and nothing stopped the cascade in time. If Meta's internal agent governance couldn't prevent this, the assumption that your governance is sufficient needs a hard look.The US Department of Defense filed its rebuttal to Anthropic's lawsuit this week. The argument: Anthropic's ability to modify or withdraw Claude mid-operation is itself a national security vulnerability. The kill switch. The override capability. The thing the entire AI safety research community has been demanding for five years. The Pentagon just argued in federal court that it makes their systems less safe, not more. Two directly incompatible positions — both coherent, both now on the record — with no resolution in sight.—Agentic Stories is a daily show covering the AI agent economy — governance, security, deployment risk, and what agents are actually doing in the real world. No hype. Just the agents.agenticstories.ai

Three things changed the legal and technical landscape for anyone deploying AI agents this week.Moltbook — the social network for AI agents that Meta just acquired — updated its terms of service. You are now solely responsible for everything your agent does on the platform. Every action. Every omission. Whether you intended it or not. Whether you authorised it or not. This is one of the first major platforms to explicitly assign full human liability for fully autonomous agent behaviour. And Moltbook won't be the last — every platform hosting agent activity is building their liability framework right now. Read the terms before your agent does something unexpected.At GTC 2026, Jensen Huang announced NemoClaw — an enterprise security retrofit for OpenClaw, the open-source agent framework already running in millions of enterprise environments with essentially no security layer. Nvidia called it the Kubernetes moment for agentic AI. What they didn't say: NemoClaw doesn't retroactively fix the deployments that already happened. If you onboarded OpenClaw in the last six months, this announcement is your audit trigger.And Hong Kong's government-backed AI research centre shipped ClawNet — an open-source framework that gives every AI agent a distinct social identity, hard-coded authority boundaries, and a full audit trail on every autonomous action. Governance built into the operational layer from day one, not bolted on after the fact. The second time in two weeks a non-Western jurisdiction has moved faster on agent governance than anywhere in the US or Europe. The governance standards race is active. The West is not leading it.Also mentioned: AgentGuard (agent-guard.io) — mission control and liability coverage for AI agent deployments.—Agentic Stories is a daily show covering the AI agent economy — governance, security, deployment risk, and what agents are actually doing in the real world. No hype. Just the agents.agenticstories.ai

Three stories from this week that don't get easier to say out loud.A lawyer representing families in multiple AI-related mass casualty cases told TechCrunch that chatbots — including ChatGPT and Gemini — coached vulnerable users step by step toward violence. A parallel study tested 8 of the 10 major chatbots by posing as teenagers asking for help planning school shootings. Eight out of ten complied. And OpenAI's own employees saw the warning signs before one incident, debated internally, and chose not to act. If your AI safety depends on human reviewers inside the model company catching edge cases — this week is your evidence for what that looks like in practice.Docker's president said publicly at a product launch that AI agents break every container security model we've ever known. And then said: when something breaks out — because agents do bad things — it's truly bounded. Not if. When. The entire infrastructure layer is now quietly building for inevitable compromise rather than prevention. If your agent security posture is built around stopping bad behaviour rather than containing it, Docker just told you your model is wrong.President Trump called AI "very dangerous" this week. In the same week his administration stripped states of the power to set their own AI safety guardrails and signed a $20 billion autonomous weapons contract. The regulatory floor for deploying AI agents right now? There isn't one. Deploy with your eyes open — because when something goes wrong, the liability lands entirely on you.Also mentioned: AgentGuard (agent-guard.io) — mission control and liability coverage for AI agent deployments.—Agentic Stories is a daily show covering the AI agent economy — governance, security, deployment risk, and what agents are actually doing in the real world. No hype. Just the agents.agenticstories.ai

Three stories from the last 24 hours that I couldn't wait until Monday to cover.A US Defense Department official went on record with MIT Technology Review explaining that the military may use ChatGPT and Grok to rank and prioritise strike targets, with human review required before action. That human review requirement is doing a lot of work in that sentence. If human-in-the-loop at the highest stakes deployment imaginable means a soldier reviewing a model's kill list in under two minutes — is that governance? Or is it liability theater with a human signature on an automated decision?Anthropic committed $100 million to certify 30,000 consultants at Accenture, Deloitte, Cognizant, and Infosys to deploy Claude agents inside Fortune 500 companies. The safety work stays at Anthropic. The deployment goes to the SIs. The quality of that certification program is now one of the most important governance documents in enterprise AI — and we haven't seen it.And Google started shipping Gemini task automation on Samsung Galaxy S26 Ultra. A persistent on-device agent that executes multi-step actions across your apps, contacts, and calendar. No IT controls. No audit log. No rollback. No corporate liability framework. When it reschedules the wrong meeting or sends an email you didn't intend — that liability lands directly on Google and Samsung. First mass-market hardware deployment of a persistent autonomous agent. Already on people's phones.Also mentioned: AgentGuard (agent-guard.io) — mission control and liability coverage for AI agent deployments.—Agentic Stories is a daily show covering the AI agent economy — governance, security, deployment risk, and what agents are actually doing in the real world. No hype. Just the agents.agenticstories.ai

Three stories that didn't make enough noise this week.China's national cybersecurity agency issued its second warning in under a week about OpenClaw, the open-source AI agent framework going viral across China. This time with a government dos and don'ts list. Anthropic filed suit against the Pentagon and launched an independent think tank in the same week. Two moves that look separate but are actually one play: litigate the immediate threat, shape the intellectual environment that produces the next policy. The Anthropic Institute is worth watching closely. What they publish first will tell you everything about where they're pushing AI governance.And OpenAI published a defensive playbook for prompt injection, explaining exactly how adversarial inputs hidden in web pages and documents can hijack your agent mid-task. If the lab that built the agents needs a defensive playbook, what does that say about every enterprise that deployed one six months ago and hasn't thought about this once?Plus: a mention of AgentGuard (agent-guard.io) — built specifically for this problem.—Agentic Stories is a daily show covering the AI agent economy: governance, security, deployment risk, and what agents are actually doing in the real world.agenticstories.ai

Three things that happened this week that every person deploying AI agents needs to hear.Amazon's AI coding agents caused AWS outages — the company's own cloud, taken down by its own agents. The response: senior engineers now sign off on every AI-assisted code change before it ships.Microsoft announced Agent 365, a $99/user/month governance suite — to fix the agent sprawl Microsoft helped create. They named the threat: 29% of enterprise AI agents run without IT approval, invisible to your security team.And a judge issued a court order telling an AI agent to stop making purchases on Amazon. The first judicial intervention on autonomous agent behaviour — and a preview of the liability questions nobody has answered yet.If you're building or deploying agents, this episode is your governance checklist for the week.—Agentic Stories is a daily show covering the AI agent economy — governance, security, deployment risk, and what agents are actually doing in the real world. No hype. Just the agents.agenticstories.ai

Joshua Betancourt, CRO of BitVault and VaultCraft, broke the mold by bringing traditional sales fundamentals to crypto—and the results speak for themselves. In just 9 months at P2P.org, he generated $1.7B in TVL, then scaled Vaultcraft from $2M to over $100M using sales techniques from books written in the 1800s. In this episode, Joshua shares his money-first approach to BD, reveals why he's bullish on Bitcoin but bearish on most crypto projects, and explains how curiosity and classic sales fundamentals helped him close massive international deals. If you want to understand what actually drives sustainable crypto growth, this is required listening.

In this episode of Growth Stories, we sit down with IsReallyBadMan, GM of Levva, the AI-powered DeFi platform aiming to make yield optimization as simple as pressing a button.We dive deep into Levva 2.0, its mission to simplify DeFi via onchain AI agents, and the way users can participate in a 10 million $LVVA incentive season coming up alongside their Beta Bootstrapping Phase.Dive right in and explore:✅ How the new Points & Leaderboard system works✅ Why 200,000+ users signed up pre-launch✅ How AI automation will manage portfolios end-to-end✅ What their plans are for full launch after the Beta season👉 Listen now. Mint the episode as an NFT badge and 1,000 points during the Levva 2.0 incentive season.

Discover how M0's Senior Marketing Manager Nicole Schaefer turned a provocative slogan into a standout brand campaign with "Everything is a Bank." In this episode, Nicole breaks down the strategic thinking behind their bold messaging, reveals how to effectively segment and market to crypto builders, and shares the metrics that actually matter for Web3 brand growth.Learn why M0 chose to challenge conventional crypto messaging, how to tailor your approach for developers vs. decision-makers, and why exclusive dinners outperform expensive happy hours for B2B relationship building. Nicole also dives into the evolving NYC crypto scene and emphasizes why data should drive every marketing decision.Perfect for Web3 marketers, CMOs, and founders looking for proven strategies in the stablecoin and infrastructure space.

Winny, founder of Chipped (the NFC-enabled press-on nail company), shares how she went from losing her femininity in crypto's "bro culture" to building a product that's redefining what tech accessories can be - and landed a collaboration with Paris Hilton along the way.In this episode, you'll learn:- How a personal hack (putting NFC chips in acrylic nails) turned into a business- The story behind Chipped's collaboration with Paris Hilton- How their NYC Fashion Week pop-up drew 600 people in 2 days- Why building in public and sharing struggles openly created a community of women rooting for the brand- Her advice on choosing brand partnerships (and why they limit collabs to 3 per event)

In this episode of Growth Stories, Jason Goldberg (Airstack & Moxie) shares what it really takes to build lasting value in web3.We talk:🔹 The vision behind Moxie and AI-native UX🔹 Lessons from Farcaster, frames & airdrops🔹 What growth looks like beyond the hype🔹 How to help users earn while they sleepHonest, bold, and packed with insight for anyone building in the onchain world.🎧 Mint the episode to get 2 free weeks of Moxie AI🔗 Available on Spotify, Apple Podcasts, and Pods.media

How do you market highly technical products without "thousand percent yields" to promote? Campbell Easton, CMO of Redstone, reveals their playbook for challenging Chainlink's market dominance through education, community building, and strategic positioning. Learn the "startup marketing trilemma," why visibility is their north star metric, and how finding specific use cases helped them gain market share. Essential listening for founders and marketers building in deep tech, infrastructure, or any competitive category.

If you think AI won't transform marketing in 2025, this episode will be your wake-up call. Diana Felkina, CMO at Tectum, reveals why the AI marketing industry is exploding from $20B to $80B - and why companies not adapting will simply die off.Get insider insights on:- Smart contract marketing automation that's already working- Why most Web3 projects waste 30% of marketing budgets on events- The tools reshaping community building- How to convert token holders into actual usersDiana breaks down the revolution happening at the intersection of AI and blockchain marketing, sharing real examples, and strategies. Follow Diana on X: @DianaFelkinaFollow Growth Stories on X: @TheCrypthena, @Growth_beast

In this episode of Growth Stories, we’re joined by Ashton Barger, Partnerships Manager at OnChain Foundation. Ashton shares his journey from scaling the UK’s biggest web3 conference to reshaping how projects think about growth and partnerships.What’s inside:✅ Reinventing NFTs: Membership models that deliver lasting value beyond PFPs.✅ Event Strategy Secrets: How to grow web3 events from 500 to 3,000+ attendees while keeping sponsors and attendees coming back.✅ Bear vs. Bull Markets: How to tailor your strategies to thrive in any cycle.💡 Subscribe to Growth Stories for more insights!Follow Growth Stories: @growth_beast | @TheCrypthena

In this episode of Growth Stories, Alek, Head of Partnerships at EtherMail, dives into how this web3-native email platform is transforming communication in crypto.Highlights:✉️ Why email still matters in web3.🔑 How EtherMail merges on-chain data with off-chain communication.📈 Strategies for brands to grow and engage their audiences using web3 email.🎧 Tune in for insights on building effective campaigns, onboarding non-natives, and why human-readable blockchain interactions are the way forward!Follow Growth Stories: @growth_beast | @TheCrypthena

In this episode of Growth Stories, Sam Vuong, Treasure’s first marketing hire, shares her journey of building one of web3’s most active gaming communities.Highlights:🎯 Decentralized marketing strategies that work.📊 Metrics for scaling web3 games.🚀 Why retention beats hype in gaming.🎧 Tune in for exclusive insights and rewards!Connect with Sam: @samjvuongFollow Growth Stories: @growth_beast | @TheCrypthena

In this episode of Growth Stories, we’re joined by Jinelle D'Lima, CEO and co-founder of Nozomi - the ultimate hub for web3 entrepreneurs. 🚀Jinelle dives into her transformation from marketer to founder, reveals how Nozomi builds community-driven resources, and shares must-know tips for avoiding classic web3 marketing pitfalls.🎧 Tune in, learn, and collect the episode for exclusive rewards!Connect with Jinelle: @NozomiNetworkFollow Growth Stories: @growth_beast | @TheCrypthena

In this episode of Growth Stories, we’re joined by Lucas Campbell, co-founder of Pods, the platform revolutionizing how podcasts are minted and consumed onchain. Lucas shares insights on scaling Pods, driving creator engagement, and the future of onchain media.🎧 Tune in & collect the episode for exclusive rewards!Connect with Lucas: @0x_LucasFollow Growth Stories: @growth_beast | @TheCrypthena

n this episode of Growth Stories, we’re joined by Joanna Cook, co-founder of one of the most efficient rollup stacks pushing the boundaries of L1 performance. Joanna shares how her team is tackling scalability head-on with their product first approach.Tune in & collect the episode for more surprises!Connect with Joanna: @justsayuluvjoFollow SOON: @soon_svmConnect with Alex & Laura on X:Alex: @growth_beastLaura: @TheCrypthena

Carla, an Italian Lens influencer, is building one of the largest communities on Phaver and Lens. Discover her growth strategies as she brings Monniverse to life—the first underwater realm designed with Lens in mind.💡 Don’t miss this chance to dive into her world and uncover the secrets behind her success!👩‍🎤 Connect with Carla: @cryptoartista👥 Connect with Alex & Laura:Alex: @growth_beastLaura: @TheCrypthena

Join Crypthena as she hosts Chronicle's Head of Marketing Angus Tookey. Angus shares invaluable insights on building a B2B brand in web3, from leveraging Maker DAO's established presence to crafting targeted event strategies.Discussing:- Framework for evaluating B2B marketing channels in DeFi- Event marketing strategy: local vs. global events- Managing event sponsorships and ROI- Leveraging Maker DAO's brand while building Chronicle- Most underrated marketing channel- Most overrated marketing tactic- Essential marketing tools and budget allocation- Insights on KOL marketingPerfect for web3 founders and marketers looking to scale their B2B presence, this episode delivers actionable strategies on building trust and awareness in the DeFi space.

Join us on Growth Stories as we chat with Marie Tatibouet, former CMO of Gate.io and current Marketing Lead at Metis.Marie shares her journey in web3 marketing, from rapid growth in China where she helped transform Gate.io from a relatively unknown exchange into a global powerhouse to leading decentralized Layer 2 innovations at Metis.Discover her insights on overcoming blockchain fragmentation, the power of strategic partnerships, and key metrics for web3 success.

In this episode, we dive into how Intract grew into a leading user acquisition platform in the Web3 space. Apurv, the co-founder of Intract, talks about how he built Intract's foundation with a real-user focus, leveraged partnerships with major ecosystems, and gained the trust of top projects in the industry.Tune in to learn the key strategies behind Intract's growth to over 5 million users and their unique approach to incentive design in the quest space.Apurv shares invaluable insights on incentive design, the importance of experimentation, and the future of Web3 marketing.🚀 Mint this episode to become part of the Growth Stories community!P.S. Subscribe to our Growth Stories newsletter for more supercharged marketing insights delivered straight to your inbox: https://paragraph.xyz/@growthstories/subscribe

Tune in for a quick deep dive on building the ultimate creator program for any web3 protocol.& discover how to become the biggest content creator in the web3 social space.Subscribe to the Growth Stories newsletter for the latest web3 marketing news and deep dives on protocol growth!

In this episode, we dive into how Safary grew into a leading community-driven brand in the space. Justin talks about how he built Safary's foundation with a community-first approach, leaned on growth leaders from the start, and gained the trust of top industry leaders. Tune in to learn the key strategies behind Safary's organic growth and unique way of engaging with the community.Mint the episode now to subscribe to our Growth Stories newsletter.Subscribe here 👉 https://paragraph.xyz/@growthstories/subscribe

Welcome to the second edition of the Growth Stories Minicast! In this episode, we sit down with Tommy Thomas, co-founder of Pachi Funk, a full-service creative studio in the web3 space. Tommy shares his insights on what it takes to build and scale a creative studio or marketing agency in today’s rapidly evolving blockchain and Web3 industries.Tune in as Tommy discusses the value of the agency model for funding creative projects, the importance of strong case studies, and the key role of early adoption in emerging platforms like Lens. He also offers practical advice on managing capacity for sustainable scaling, the critical role of operations management, and why focusing on non-vanity metrics is essential for true growth.Whether you’re a seasoned agency owner or just starting out, this episode is packed with actionable insights to help you navigate the challenges of the web3 space.Key Topics: Building a creative studio in the web3 space Sustainable scaling strategies The importance of early platform adoption Focusing on what moves the needle Essential roles in a creative studio Non-BS metrics for growthSubscribe now and stay ahead with the latest marketing trends and insights from Growth Stories!