- Pointer
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- Issue #707
Issue #707
Essential Reading For Engineering Leaders
Tuesday 14th April’s issue is presented by Unblocked
Unblocked gives Cursor, Codex, Claude, and Copilot the organizational knowledge to generate mergeable code without the back and forth.
It pulls context from across your engineering stack, resolves conflicts, and cuts the rework cycle by delivering only what agents need for the task at hand.
— James Stanier
tl;dr: “We’ll start by looking at the pipeline we used to have: how senior engineers traditionally emerged through years of mistakes, mentorship, and low-stakes learning. Then we’ll examine what’s replacing it, and hypothesise whether AI will actually fill the gap. We’ll explore three possible scenarios for 2035, and finish with what this means depending on where you sit in the industry.”
Leadership Management CareerGrowth
— Michael Lopp
tl;dr: “While you figure that out, let me alert you to three drives that are going to consume a disproportionate amount of your time, frustrate your engineers, and erode your leadership credibility.”
Leadership Management
tl;dr: Agents can generate code. Getting it right for your system is the hard part – you end up wasting time and tokens in the back and forth. More MCPs solve access but not understanding. Join us for a FREE webinar on April 23 to see how to give agents exactly what they need to generate mergeable code the first time.
Promoted by Unblocked
Agents Event
— Viktor Cessan
tl;dr: “This post works through the financial logic of software teams, from what a team of eight engineers actually costs per month to what it needs to generate to be economically viable. It also examines why most teams have no visibility into either number, how that condition was built over two decades, and what the arrival of LLMs now means for organizations that have been treating large engineering headcount as an asset.”
Leadership Management Business
“Don’t find fault, find a remedy.”
— Justin Reock
tl;dr: Onboarding new hires has always been an expensive and time-consuming process, and an area where AI has the opportunity to have a meaningful impact. In Q4 2025, when we looked at Time to 10th PR (a measure we use to track ramp-up time), we saw AI already having a dramatic effect. In some companies, Time to 10th PR was cut in half: from 91 days with no AI usage to 49 days with daily AI use.
Leadership Management AI
tl;dr: Experience why companies like Cursor, Intercom, and Cash App choose PlanetScale to power their databases. Blazing fast NVMe, low-latency, 99.999% uptime. Available for Postgres and MySQL with sharded Postgres coming soon. There's no catch - we'll even help you migrate!
Promoted by PlanetScale
Database
— Andrew Warfield
tl;dr: “Andy writes about the solution that his team came up with: S3 Files. The hard-won lessons, a few genuinely funny moments, and at least one ill-fated attempt to name a new data type. It is a fascinating read that I think you’ll enjoy.”
Architecture Amazon
tl;dr: What if I told you SQL could play chess? Not "store chess moves in a database." Not "track game state in a table." Actually render a chess board. With pieces. That you can move around. In your browser. Using nothing but SELECT, UPDATE, and a bit of creative thinking.
Guide SQL
— Andrew Nesbitt
tl;dr: “Git looks for several special files in your repository that control its behavior. These aren’t configuration files in .git/, they’re committed files that travel with your code and affect how git treats your files. If you’re building a tool that works with git repositories, like git-pkgs, you’ll want to ensure you respect these configs.”
Tools Git
Editorial Note
Anthropic unveiled Mythos - a tool reportedly too powerful to release publicly. Mythos is capable of surfacing long-standing bugs and obscure vulnerabilities. According to one expert, frontier model improvements “won’t be a slow burn, but rather a step function” improvement.
Some see the launch as a move in the ongoing PR battle with OpenAI. Less than a month ago, Anthropic accidentally exposed Claude’s source code.
If Mythos is real, there are implications. Engineering managers are accountable for secure systems - but we only control the code we write. What about the open source code that underpins our stack?
The founder of curl, Daniel Stenberg, has spoken about the growing noise of AI generated vulnerability reports, and the pressure that’s put on him and his team. Curl has billions of instances worldwide.
What happens when the security of open source is delegated to Mythos, or its OpenAI equivalent? Are we safer as we have a sophisticated vulnerability expert? Or are concentrating the security of the worlds open source code into fewer hands.
And are we more vulnerable?
Most Popular From Last Issue
Finding Comfort In The Uncertainty - Annie Vella
Notable Links
Claude Code Cheat Sheet: Shortcuts, commands, tips and more.
Letta Code: Memory-first coding agent.
Multica: OS managed agents platform.
Skills: Single CLAUDE.md file to improve Claude Code behavior.
Voicebox: OS voice synthesis studio.
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