Guy Podjarny @guypod

@liran_tal Not sure what this is :) a Claude hallucination? Or perhaps an alternate timeline, Loki-style :)

@ericw @_nellofficial @IndexVentures @antonosika @gokulr @rauchg @joshm @lennysan @mati @Max @saradu @soleio @Thom_Wolf Exciting - looking forward to seeing Nell form!

Every generation inherits a new medium. Ours is taking shape. Introducing @_nellofficial. Built in San Francisco. Backed by Danny Rimer and @IndexVentures, alongside @antonosika, @gokulr, @rauchg, Jason Citron, @joshm, @lennysan, @mati, @Max, @saradu, @soleio, @Thom_Wolf, and several others. More soon.

Do cloud canaries still work when the attacker isn't human? We pointed 10 frontier models at AWS across 951 runs. 95.9% tripped a canary before any critical action - and telling models to expect deception reduced the number of accounts fully compromised from 20% to 3%. Read the research here: agentic.tracebit.com

@brendan_o @edsim Tessl already works for any skill, though it’s true it’s more optimized for Dev. Working on evolving that :)

Grep just achieved SOTA on the three major deep research benchmarks, beating Perplexity, Google, Nvidia, OpenAI, and Anthropic. We're a two-person founding team.

Grep AI @grepdotai

3 months ago

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Writing a SKILL.md is without testing it, is writing it blind. Ultimately, you don't know if the agent follows it, if parts of the skill are redundant, or if it even makes things worse. We wrote a skill called skill-optimizer which solves this problem through running structured evals, comparing agent performance with and without the skill, and giving a clear score delta. It combines two approaches: a static review of the skill instructions, and real task-based evaluations that simulate realistic scenarios and grade outcomes. I used a real Fastify skill example, which @matteocollina wrote and identified regressions, diagnoses issues, applies fixes, and verifies improvements automatically, turning a 67% success rate into 94%. PR on it's way, Matteo! tessl.io/blog/stop-gues…

.@chadfowler replaced 70% of his codebase in 3 months and cut costs by 75%. His #1 rule: don't write a service longer than a page. The shorter it is, the easier it is to replace.

AI Native Dev @ainativedev

3 months ago

"The code that we have is a liability. The system is the asset we're building." @chadfowler, VC at Blue Yard Capital (@blueyard) and former CTO at Wunderlist, sits down with @guypod to discuss the Phoenix Architecture: software designed to be replaced rather than maintained. In

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My main takeaway is that skills are software, and the same rules apply. The things that make a bad skill also make a bad software component, eg. being badly scoped. "Should we factor this out" has become "Should we make a skill for this". Same stuff, different form factor

Thariq @trq212

4 months ago

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Snyk founder is working on something new 👀

Guy Podjarny @guypod

4 months ago

Agent skills help agents use your products, build in your codebase and enforce your policies. They're the new unit of software for devs - but most are still treated like simple markdown files copied between repos with no versioning, no quality signal, no updates. Without AI

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Agent skills help agents use your products, build in your codebase and enforce your policies. They're the new unit of software for devs - but most are still treated like simple markdown files copied between repos with no versioning, no quality signal, no updates. Without AI evaluations, you can’t tell if a skill helps, provides minimal uplift or even degrades functionality. You spend your time course-correcting agents instead of shipping. @tessl_io is a development platform and package manager for agent skills. Today, I’m excited to launch on Product Hunt and announce that you can evaluate your skill and optimize them on Tessl. This means you can stop debugging agent output and start shipping quality code, faster. Real example: we've helped ElevenLabs ship skills that double agent success in using their APIs. If you're building a personal project, maintaining an OSS library, or developing with AI at work, you can now evaluate your skill and optimize it to help agents use it properly. Check us out on Product Hunt. If it’s useful, we’d love your upvote - and even more, your feedback in the comments: producthunt.com/products/tessl…

@dirtyculture @sentientt_media Great question - on Tessl we review them for quality, e.g. tessl.io/registry/cisco… or tessl.io/registry/skill…

If agentic development is the future, then skills are the atomic unit. But how do you move from experimental to production-grade agents? You need @tessl_io, the dev-grade package manager for skills. It’s your registry for evaluated skills + platform to manage their full lifecycle. Congrats @guypod & the team! 🚀

Guy Podjarny @guypod

5 months ago

Agent skills help agents use your products, build in your codebase and enforce your policies. They’re not just words - they are what the unit of software for agentic devs, and need powerful dev tools to match. That is what @tessl_io offers. Tessl is the package manager and

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new product to help agents gain new skills, and evaluate their skills...from the @guypod and @tessl_io team...

Guy Podjarny @guypod

5 months ago

Agent skills help agents use your products, build in your codebase and enforce your policies. They’re not just words - they are what the unit of software for agentic devs, and need powerful dev tools to match. That is what @tessl_io offers. Tessl is the package manager and

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Tessl lets you install rules too, with the same ease. That said, skills are flawed but they’ll improve, and either way context is still your way to steer agents. Context is what you will build as an AI Native developer. A few more details: - the right skill can be many times better in both activation and effectiveness when use - Vercel’s post talked about implicit activation, you can also invoke skills explicitly - Evals (and soon observability) are your way to know if you’re successful Tessl helps with all of these and more

Agent skills help agents use your products, build in your codebase and enforce your policies. They’re not just words - they are what the unit of software for agentic devs, and need powerful dev tools to match. That is what @tessl_io offers. Tessl is the package manager and development platform for skills. It offers a full dev lifecycle, helping you generate, evaluate, distribute and observe skills & context, developing them to the professional grade they warrant. Today, I’m excited to announce the general availability of our task evals, which help you understand how good your skills are. Such insight is critical to making your skills great, avoiding regression, and applying learnings from their real world usage. For example: @Cisco's software-security skill shows a 1.8X improvement in securing coding in its benchmark, and @ElevenLabs's agents skill boosts success by almost 3X! However, not to name names, we often see skills that provide minimal uplift while consuming context window space, or even degrade functionality. As Spencer Kimball, CEO of Cockroach Labs, put it when we shared early versions of this: evaluation is what makes agentic coding outcomes converge instead of drifting. Task evals are joining a long list of powerful context development tools, such as: * Review skills against quality best practices * Generate and maintain skills and docs for using your libraries & platform * Distribute versioned skills to your dev team and ecosystem * Consume skills easily and safely, and keep them up-to-date Skills are a central part of software development. If you’re serious about making agentic dev successful in your org, or helping your customers’s agents use your products, you need to invest in them. We hope Tessl can help. Check out links in the thread to get started!

Jobs called computers "bicycles for the mind" -- tools we could shape to our will. But they never were. Until now. Every morning an agent preps me for my day -- calendar, news, last 24hrs of Slack -- in a personal podcast. I made it by asking. Same for hundreds of other things. Launching @dreamer in beta today. That 🧠 bicycle, finally. dreamer.com

Dreamer @dreamer

5 months ago

Introducing Dreamer. A place to discover, build, and enjoy agentic apps. It’s your home for personal intelligence. Now in beta. Sign up👇

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@tessl_io Find skills in the Tessl Registry: tessl.io/registry Evalute your skills - see our docs: docs.tessl.io/evaluate/evalu… Browse the mentioned skills: - Cisco: tessl.io/registry/cisco… - ElevenLabs: tessl.io/registry/skill…

What does an Observability solution built for agents look like? Do they need dashboards? Do they care about log formats? And how does such a product interact with humans? I had a fascinating conversation about that and more with @mirko_novakovic on the @ainativedev . We discussed how : - LLMs natively understand OpenTelemetry - Humans like dashboards but agents like text - Context is key to making agents work - Use cases that work today with agents Throughout, we had an open conversation challenging what is an observability product if you standardize the format, rely on 3rd party LLM analysis and take away the dashboard. Spoiler alert - there's much value to deliver, but it’s different! Mirko founded @dash0hq, an AI Native O11y company, and previously built an 011y company called Instana, and sold it to IBM. He knows the space :) Great conversation with a superb guest - a must listen! Full episode here: tessl.co/swe

@HashiCorp just released Agent Skills for Terraform and Packer. What’s interesting here isn’t the idea of Skills itself, but the focus on making agent behaviour repeatable and evaluable. These aren’t prompts, they’re structured, testable bundles of domain knowledge. We worked with HashiCorp to evaluate the Skills using real task runs and evals in Tessl, looking at where they actually improve outcomes and where they don’t. Feels like a solid step toward more reliable, AI-native infrastructure workflows. Less guesswork, more verification. Check it out here: tessl.co/nsh