chad fowler

programmer, general partner @blueyard, author of upcoming book Crypto & Web3: The Good Parts. prev @wunderlist, @microsoft, @rubycentral, @rubyconf @railsconf

[chad fowler @chadfowler]

Regenerative Software

https://t.co/hjAujJNL1f

[chad fowler @chadfowler]

@sergefdrv I could send you a draft of my upcoming book. Or check out https://t.co/tjzQgwRuy9 for the blog version which isn’t as deep but catalyzed it.

[chad fowler @chadfowler]

In the year 2027 it will be seen as irresponsible for humans to write their own code and insanely inefficient for humans to review all code created by agents

Come hear me speak in London on June 1st so you can either listen to why I believe this is true and how we make this okay or at least yell at me in the hall afterward  😅

[AI Native Dev @ainativedev]

What if the future of software isn’t maintaining systems… but continuously rebuilding them?

Chad Fowler ( @chadfowler ) is joining AI Native DevCon London 2026 with one of the most thought-provoking architectural conversations of the event.

A technologist, investor, author, and longtime voice in software engineering, Chad has spent decades shaping how developers think about systems and careers. From co-founding Ruby Central to leading engineering organizations at Microsoft and Wunderlist, his work has consistently challenged industry assumptions.

Now, through what he calls Phoenix Architecture, he’s asking a much bigger question.

What changes when software becomes easier to regenerate than to fully understand?

In his session, An Architectural Approach to Regenerative Software, Chad explores how AI is shifting the economics of software development and why many of our existing assumptions about stability, maintenance, and architecture may no longer hold.

What this session explores
• Why AI changes the balance between maintenance and regeneration
• How to think about systems where implementations are constantly replaceable
• What parts of software architecture actually need to remain stable
• How trust, durability, and coherence evolve in AI-native systems
• The human costs of instability and what architects must protect

This isn’t a framework talk or a checklist. It’s a deeper exploration of how software engineering itself may need to evolve as agents reshape the mechanics of building systems.

If you enjoy talks that challenge foundational assumptions and leave you thinking long after they end, this is one to catch.

Join us in London or online: https://t.co/Kl88dtYu4R (use AIND-X-BB-20 for 20% discount)

[Winkle @robbwinkle]

This is a must read https://t.co/rqUutUntJd. The hidden gem to @chadfowler's writing is amazing as well.

Both add more depth to my own thoughts. Thanks @mipsytipsy

[Irina Nazarova @inazarova]

I published https://t.co/nTX5Jc022z Ruby LLM Discoverability Scorecard after watching @chadfowler 's talk at @RubyConfAT - to ensure that we, the @rubylangorg and @rails community, do our best to be in training data and in agent retrieval. Just updated the data. Here's what's improved in 30 days:
- llms.txt +3: @_maintainable , @AppSignal , @flydotio
- content negotiation +1 @AppSignal
- .md route:+1 @AppSignal
- sitemap: +2 @bridgetownrb @any_cable
- robots allows AI: +1 Karafka @maciejmensfeld

Good job!

[chad fowler @chadfowler]

@sergefdrv Flights got screwed by weather and I missed it :(

[chad fowler @chadfowler]

@inazarova An amazing honor! Enjoy Matsue!

[Irina Nazarova @inazarova]

Nothing special, just me keynoting at #RubyWorld in Japan alongside the author of Ruby 🤩🤩🤩 (srsly, I’m blown away!)

[Steve Krouse @stevekrouse]

@chadfowler my pleasure!

you might like this https://t.co/1kJOTP0Uhw

just found it, and thought it's a pretty good argument in favor of the spec line of thought

[chad fowler @chadfowler]

Thank you for taking the time and energy to read, process, and critique!

I have answers on the spec == code thing. They might be wrong but they also aren't just code. Short version: my thinking is that specs are evolving metadata with, among other things, real production runtime output as input.

Specs are extracted from natural language (or even code) and then my bias is to store these as nodes in a graph. Specs are never static. We now have the advantage that LLMs can process lots of text, make semantic inferences, and help us fill the gaps of what a full spec really needs, over time.

I don't think eg new programming languages for specs are a good idea. They might be a good intermediate representation if plugged into a proper ontology system so you could do semantic type checking etc but I think the quest to create the perfect language for specifications leads exactly to the punch line of that comic.

[Steve Krouse @stevekrouse]

I did a deep dive into @chadfowler's Phoenix Architecture, and wrote up my thoughts on what it means for code to be cheap to generate https://t.co/xFzFP5B3WJ

[chad fowler @chadfowler]

Thank you for taking the time and energy to read, process, and critique!

I have answers on the spec == code thing. They might be wrong but they also aren't just code. Short version: my thinking is that specs are evolving metadata with, among other things, real production runtime output as input.

Specs are extracted from natural language (or even code) and then my bias is to store these as nodes in a graph. Specs are never static. We now have the advantage that LLMs can process lots of text, make semantic inferences, and help us fill the gaps of what a full spec really needs, over time.

I don't think eg new programming languages for specs are a good idea. They might be a good intermediate representation if plugged into a proper ontology system so you could do semantic type checking etc but I think the quest to create the perfect language for specifications leads exactly to the punch line of that comic.

[chad fowler @chadfowler]

lol. Maggie please let me know so I can also learn what I think about it :)

[Steve Krouse @stevekrouse]

i need @Mappletons to write about @chadfowler's phoenix architecture so i can figure out what i think about it

[chad fowler @chadfowler]

@stevekrouse @Mappletons Also how did I not already follow you, Steve?

[Index Network @indexnetwork_]

https://t.co/ORWOQk4rgc

[Irina Nazarova @inazarova]

Watch this learn Ruby founder stories of @Cole__Robertson @avinashjoshi @paolino @kieranklaassen @andywang - all building new fantastic products on Rails today✨ and what @chadfowler ‘s talk has triggered me to do 🥵

[chad fowler @chadfowler]

@alediaferia You're right about all of it. Now it's just a matter of completeness and speed.

[chad fowler @chadfowler]

For most of software history, production has been the end of the pipeline.

Build.
Test.
Deploy.
Run.

We’re approaching a world where production becomes the beginning of the next iteration.

[Omer Shlomovits @OmerShlomovits]

Introducing HyperQuant: A new Lattice-based compression algorithm that significantly improves LLM key-value cache memory over TurboQuant and OCTOPUS, and with higher accuracy!
But it gets better - we apply the same compression technique to weights, outperforming Higgs!
Finally, (for the first time ever?), we show how to compress video DiT weights. demo on LTX-2.

Easy to integrate: we release a reference kernel code with the paper, under MIT license. This is a calibration-free, post-training quantization. Disclaimer: performance will get much better in next releases.

Links and key results in next tweet.

[chad fowler @chadfowler]

Every bug report, support ticket, incident, and customer request is a specification.

We just haven’t had systems that could consume them directly.

https://t.co/t19d6XVuLa

[chad fowler @chadfowler]

Most of software engineering is the process of discovering the difference.

[chad fowler @chadfowler]

The first version of a system reflects the designer’s understanding of the problem.

The tenth version reflects reality.