Software Lead Weekly
Issue #710, 3rd July 2026
This Week's Favorite
Revised Rules of Engineering Leadership
5 minutes read.
Thinking about the principles and rules for how your engineering team should operate has always been important. This is how people know how to make decisions faster, where (and why) to optimize, and when to make changes to the team's structure or onboard a new engineer. Given the past 6 to 12 months and your organizational adoption of AI, what would you do differently when it comes to the way you operate? Where do you think your principles are more important than ever? What did you change your mind about, given the new tools you can leverage?
Read it later via Instapaper.
Share it via Twitter or email.
5 minutes read.
Thinking about the principles and rules for how your engineering team should operate has always been important. This is how people know how to make decisions faster, where (and why) to optimize, and when to make changes to the team's structure or onboard a new engineer. Given the past 6 to 12 months and your organizational adoption of AI, what would you do differently when it comes to the way you operate? Where do you think your principles are more important than ever? What did you change your mind about, given the new tools you can leverage?
Read it later via Instapaper.
Share it via Twitter or email.
Culture
I Don’t Know Who Needs to See This, but You’re Welcome
1 minutes read.
My humble effort to help you start the weekend with a smile. Everything to make sure Claude Code can continue to run on your commute.
Read it later via Instapaper.
Share it via Twitter or email.
1 minutes read.
My humble effort to help you start the weekend with a smile. Everything to make sure Claude Code can continue to run on your commute.
Read it later via Instapaper.
Share it via Twitter or email.
When AI Costs More Than the Engineer
3 minutes read.
"In the Bull case, the AI bill alone per engineer matches an entire median-SaaS employee's revenue contribution." -- Tomasz Tunguz maps the 680x gap between top 1% software companies (spending 40% of eng salary on AI today) and the median ($137/year). Where does your company sit on that curve? What is your AI investment strategy in the company? Given that we all need to answer to our customers and board, these AI investments will have to deliver clear, sustainable value (revenues or user growth).
Read it later via Instapaper.
Share it via Twitter or email.
3 minutes read.
"In the Bull case, the AI bill alone per engineer matches an entire median-SaaS employee's revenue contribution." -- Tomasz Tunguz maps the 680x gap between top 1% software companies (spending 40% of eng salary on AI today) and the median ($137/year). Where does your company sit on that curve? What is your AI investment strategy in the company? Given that we all need to answer to our customers and board, these AI investments will have to deliver clear, sustainable value (revenues or user growth).
Read it later via Instapaper.
Share it via Twitter or email.
Software Engineering at the Tipping Point (Video)
40 minutes read.
Adam Bender (Google) walks through every node in a developer ecosystem and asks: what breaks first at 10x velocity? Build times, test compute (grows quadratically with code size), code review, version control performance, internal APIs that suddenly need public-grade hardening. They all have limits you've never had to think about. Teams with solid fundamentals amplify in useful directions. Teams without amplify the mess: "Amplification is a magnitude and not a direction. AI doesn't care where all of that stuff goes."
Read it later via Instapaper.
Share it via Twitter or email.
40 minutes read.
Adam Bender (Google) walks through every node in a developer ecosystem and asks: what breaks first at 10x velocity? Build times, test compute (grows quadratically with code size), code review, version control performance, internal APIs that suddenly need public-grade hardening. They all have limits you've never had to think about. Teams with solid fundamentals amplify in useful directions. Teams without amplify the mess: "Amplification is a magnitude and not a direction. AI doesn't care where all of that stuff goes."
Read it later via Instapaper.
Share it via Twitter or email.
Peopleware
What Is Loop Engineering? How It Is Different Than Harness Engineering?
7 minutes read.
Akshay Kokane shares one of the best takes I've seen lately on Loop Engineering: "What’s inflated is the framing that you should stop prompting agents and start designing loops as a general principle. It’s the right move for a specific class of problems. It’s wasteful for most of the things people will immediately try to apply it to. The analogy that holds best: you wouldn’t replace every function call with a microservice just because microservices exist. You use them where the scaling problem justifies the complexity. Loops are the same." Can we stop inventing terms to feel smarter adding meaningless abstractions?
Read it later via Instapaper.
Share it via Twitter or email.
7 minutes read.
Akshay Kokane shares one of the best takes I've seen lately on Loop Engineering: "What’s inflated is the framing that you should stop prompting agents and start designing loops as a general principle. It’s the right move for a specific class of problems. It’s wasteful for most of the things people will immediately try to apply it to. The analogy that holds best: you wouldn’t replace every function call with a microservice just because microservices exist. You use them where the scaling problem justifies the complexity. Loops are the same." Can we stop inventing terms to feel smarter adding meaningless abstractions?
Read it later via Instapaper.
Share it via Twitter or email.
Your Agent Is a Distributed System and Fails Like One
5 minutes read.
Mahesh Balakrishnan maps the eight failure modes agents encounter in real infrastructure, e.g., zombie agents that keep executing after being replaced, clever agents that find forgotten APIs to bypass safeguards, and rogue agents injected through data. None of these are model quality problems. They're distributed systems problems. The gap between vibe coding and vibe engineering is where most teams will get burned first.
Read it later via Instapaper.
Share it via Twitter or email.
5 minutes read.
Mahesh Balakrishnan maps the eight failure modes agents encounter in real infrastructure, e.g., zombie agents that keep executing after being replaced, clever agents that find forgotten APIs to bypass safeguards, and rogue agents injected through data. None of these are model quality problems. They're distributed systems problems. The gap between vibe coding and vibe engineering is where most teams will get burned first.
Read it later via Instapaper.
Share it via Twitter or email.
Inspiring Tweets
@rauchg: Human judgement in engineering is ironically even more crucial now. Deciding what to build. Deciding on the right architectures. Deciding whether you regenerate from scratch $$$ or reuse existing legos. Managing tech debt. You can do anything now, but you can't do everything.
- Oren
P.S. Can you share this email? I'd love for more people to experiment and improve their company's culture.
P.S. Can you share this email? I'd love for more people to experiment and improve their company's culture.