Systems | Development | Analytics | API | Testing
Modern Software Development For Today's Systems & Applications
Run Local LLMs on Mac to Cut Claude Costs
Part of the motivation for this post is how cloud API economics are shifting: Anthropic is moving large enterprise customers toward per-token, usage-based billing (unbundled from flat seat fees), which makes “always call the API” a moving cost line for teams at scale. A hybrid or local layer is one way to keep spend bounded while you still use premium models where they matter.
IBM Vault Alternatives to Consider in 2026
HashiCorp Vault (now also referred to as IBM Vault or IBM HCP Vault) has been a default secrets management choice in engineering-heavy organizations for nearly a decade. However IBM's acquisition of HashiCorp has prompted a wave of reassessment and led to consideration of other tools like SplitSecure which are likely more cost effective for most orgs. . IBM has a mixed record of supporting acquired products over the long term. Roadmap direction, licensing changes, and support responsiveness are all open questions for customers planning multi-year deployments.
SpotDevOps: Building an AI-Native SDLC Platform at ThoughtSpot
4,096 Tasks completed 89.8% success rate 302 Active users 4× growth Jan→Mar 86 Agents deployed 73 built by engineers 72 days In production 15,896 messages Modern engineering teams face a familiar paradox: the bigger the system, the more time engineers spend managing the work rather than doing it. Bugs pile up faster than they can be triaged. PRs wait days for review. On-call engineers spend hours reproducing what someone already debugged six months ago.
What the Warp Terminal Sends Home
The terminal is a developer’s most trusted tool. It sees your source code, your secrets, the commands you run in production. When a terminal adds AI and cloud features, it’s worth asking what it’s doing on the network.
Replace API Synthetics with Traffic Replay
The alert fires at 2 AM. Your observability platform’s synthetic test just failed. Login is broken. So you open your laptop, pull up the dashboard, and stare at a single red dot: the browser test. You know the problem is somewhere in the stack, but not where. Is it the auth service? The token validator? The user profile API? The API gateway timing out? You’re now about to spend the next 45 minutes correlating traces, tailing logs, and manually hitting endpoints until you find it.
Dark Code: The AI-Generated Software Nobody Understands
The biggest risk to your product isn’t AI-generated code that doesn’t work. It’s generated code that seems fine. AI doesn’t optimize for correctness. It creates something passable. Something that passes the smell test. And when everybody in the industry is pushed to move faster and do more with less, you end up shipping software that looks correct. It passed your quick visual check. It passed all the tests. But no one ever fully understood it.
Beyond AI Vibes: Deterministic Foundations for Agentic Coding
Every week there is another model drop, another agent framework, and another workflow tweak you are supposed to evaluate. Meanwhile, the largest companies, the ones operating at the highest scale and leaning hardest on AI, are also the ones making headlines for reliability strain: capacity limits, outages, and services that buckle under load.
The Hidden Cost of AI: 900% Code Churn and How to Fix It
The AI-native stack is currently facing a "Distrust Paradox": while 84% of developers use AI coding tools, trust in the results has plummeted to 29%. Ken demonstrates how to stabilize rapid software delivery by replacing unreliable "AI vibes" with a deterministic testing foundation.