The AI Native Dev - from Copilot today to AI Native Software Development tomorrow

After DevOps, Patrick Debois has a new map. The godfather of DevOps returns to walk through his AI patterns research: how he tracks where AI-native development is heading by mining social signals instead of surveys, why the stack is settling into patterns worth learning, and why your AI budget problem is really an optimization problem.

What we cover:
– Inside the AI patterns site at Tessl.io/patterns and how it's auto-generated
– The four layers of AI enablement: agent, team, platform, and organization
– Solo, shared, and multiplayer modes: the compounding effect of shared context
– Managing agent costs: budgets as a forcing function for optimization
– Scaling adoption: find the success story, don't fight the skeptics
– Hiring system thinkers instead of elegant coders

Chapters:
00:00:00 - Introduction
00:02:28 - Why AI grips Patrick Debois
00:04:33 - Agent, team, platform and org enablement
00:06:36 - Is AI-native development maturing?
00:11:19 - Inside the AI patterns site
00:18:14 - Quality, security and the IDE as review interface
00:22:45 - Changing roles and harness engineering
00:26:32 - Hiring in the AI era
00:30:31 - Scaling adoption across the org
00:42:03 - Cost management and ROI

🌐 Tessl: https://tessl.io
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Where is your organization on the maturity curve? Drop your take in the comments.
Join the AI Native Dev Community on Discord: https://tessl.co/4ghikjh

Ask us questions: podcast@tessl.io

Six people reacted to Boris's side-project Slack post. A year later, Claude Code is ubiquitous, and the company just launched its next evolution: Claude Tag, an AI teammate that lives in Slack.

Lamis Mukta, Member of Technical Staff at Anthropic, joins Simon Maple to unpack how Claude Tag works, why Anthropic built it, and what it took internally to go from a scrappy side project to a company-wide habit.

What we cover:
– What Claude Tag actually is, and how it differs from Claude Code and Cowork
– Why trust in AI agents is really a function of model capability, not just comfort
– The internal "dogfooding" culture that shaped Claude Code and Claude Tag
– How Anthropic secures multiplayer AI with agent identities and channel-level permissioning
– Where Claude and Claude Tag show up outside of engineering at Anthropic
– Dreaming: how Anthropic's managed agents continually improve their own memory

Watch Lamis' talk from AI Native DevCon London 2026 here: https://youtu.be/tTcxVv8HHNw

Chapters:
00:00:00 - Introduction
00:01:46 - Meet Lamis Mukta from Anthropic
00:02:56 - What is Claude Tag?
00:10:07 - From single-player to multiplayer agentic coding
00:15:50 - Trust, capability, and the METR chart
00:21:02 - How the industry is really using Claude Code
00:26:33 - The Claude Code origin story
00:33:47 - Agent identities and permissioning at scale
00:40:23 - Claude beyond engineering at Anthropic
00:48:16 - Dreaming and practical tips for rolling out Claude Tag

🌐 Tessl: https://tessl.io
🔔 Subscribe for weekly episodes on AI-native development

What's the one thing your team would delegate to an AI teammate first? Let us know in the comments.
Join the AI Native Dev Community on Discord: https://tessl.co/4ghikjh

Ask us questions: podcast@tessl.io

What if the whole point of your AI agent was to eventually make itself redundant? Dru Knox, Head of Product at Tessl, introduces the Tessl agent — a new interface built not just for AI-assisted coding, but for building the software factory that keeps improving without constant human input.

This is a conversation about loop engineering: how to set up automated feedback cycles so your agents get smarter, your code review gets tighter, and your team ships more without adding more toil.

What we cover:
– What the Tessl agent is and how it fits into the broader Tessl platform
– Loop engineering: why building automated feedback loops is the right place to start
– How the agent sets up and continuously improves agentic code review
– Why optimising your AI agent costs is usually the wrong lever to pull
– The case for open, modular software factories — and the risk of vendor lock-in
– UX expectations in the AI era: why outcome-oriented interfaces are now the baseline

🌐 Tessl: https://tessl.io
🔔 Subscribe for weekly episodes on AI-native development

What's your approach to building feedback loops into your agent workflows? Drop a comment — we'd love to hear how teams are thinking about this.
Join the AI Native Dev Community on Discord: https://tessl.co/4ghikjh

Ask us questions: podcast@tessl.io

Enterprises are finally being forced to care about their software development lifecycle — not because anyone suddenly got disciplined, but because agents cost money and the waste is now visible. When it was humans, it was "Timmy's just lazy." Now it's a line item. 
Simon Maple sat down with Patrick Debois (the godfather of DevOps, now DevRel at Tessl), Tammuz Dubnov (co-founder and CEO of Autonomy AI), and Daniel Jones (Head of Product at re:cinq) at AI Native DevCon London for a wide-ranging panel on AI enablement — who owns it, what's breaking, and what the organisations getting it right are actually doing differently. 
What we cover: 
– Who should own agentic coding adoption inside an enterprise, and why platform teams are already filling the vacuum 
– The "Timmy's lazy" problem: why agent cost visibility is forcing process discipline that humans never got 
– Why PR-based workflows are an anti-pattern inside enterprises once you're moving at agent speed 
– The PUMP framework (Plan, merge, polish): how one team is shipping features with developers, PMs, and designers all opening PRs –
 Rethinking what a "test" is in an agentic world — and why feedback loops matter more than first-pass correctness 
– The biggest mistake enterprises are making right now: piecemeal adoption with no mandate and no shared tooling 
 🌐 Tessl: https://tessl.io 
🔔 Subscribe for weekly episodes on AI-native development 

What's your team's approach to AI enablement — central mandate or letting individuals find their own way? Drop it in the comments.
Join the AI Native Dev Community on Discord: https://tessl.co/4ghikjh

Ask us questions: podcast@tessl.io

From the expo floor of AI Native DevCon London, Simon Maple went straight to the developers — speakers, attendees, and sponsors — to ask what's actually working with AI in 2026. The verdict? Outcomes beat outputs every time, 4,000-hour workloads are collapsing to 20 minutes, and the real bottleneck isn't code.

This is a conference floor walkthrough: honest, unscripted takes on harness engineering, evals, AI adoption mindsets, and the change management challenge that nobody talks about enough.

What we cover:
– Why measuring token usage, code commits, and outputs will lead your team astray
– How NearForm cut a 4,000-hour AML backlog to 20 minutes using agents
– Harness engineering and evals as the developer skills that matter most in 2026
– Why change management — not tooling — is the missing ingredient for real AI ROI
– How AutonomyAI is letting PMs and designers ship directly to production

Chapters:
00:00:00 - Welcome to AI Native DevCon London
00:01:03 - Chris Baty: Outcomes Over Outputs
00:05:15 - Martin: How Tooling Changed Everything
00:07:21 - Ryan: Harnesses, Evals and Skills
00:08:50 - Manny Saka: Plan Before You Prompt
00:11:58 - Cian O Maidin, NearForm: Real AI ROI
00:15:21 - Snyk: Building Trust at Scale
00:17:01 - AutonomyAI: Shipping Without Engineering
00:21:35 - Tessl Agent: Harness Engineering
00:22:41 - Closing Thoughts

🌐 Tessl: https://tessl.io
🔔 Subscribe for weekly episodes on AI-native development

Whether you're cautious or YOLOing it with AI — drop where you land in the comments.
Join the AI Native Dev Community on Discord: https://tessl.co/4ghikjh

Ask us questions: podcast@tessl.io