Dev by day, fully AI pilled. Side projects at night, build in the open, here for banter and feedback, hit or miss. Family, nature and a camera off the screen.

BTC cycle bottom: $40,600 to $50,700, 26 Sep to 31 Oct 2026. Low so far $58,525 and plenty reckon that was it. In which case I've missed the lot. My quant tool says lower. Quant's generous. Posting before the fact so it can be marked after. Egg on my face or a grin ;p
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Moinerus | Dev, AI, Crypto retweeted
man its sunday and im feeling spiritual so i wrote an article about 1. this whole renaming ai to “super intelligence” and 2. anthropic trying to convince religious leaders that ai has a soul & moral standing this feels important lmk what you think tej.as/blog/super-intelligen…
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If rolling back a release means undoing unrelated work, the batch is too big. Ship smaller batches more often. If one fails, there are fewer changes to trace and a clearer path back.
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Moinerus | Dev, AI, Crypto retweeted
- we removed unit tests in favor integration/functional tests - ci/cd invoice exploded - we removed cicd, it was slowing down our process - now our agents deploys our code - agent decided that database is going to be much faster without users future looks awesome ☠️
We deleted 800k lines of unit tests from the @sazabi monorepo earlier this week. Three hypotheses: 1- Unit tests "lock-in" slop code by making it hard to change or remove 2- Unit tests slow down dev cycles by making your agent do more work locally and by increasing CI times 3- Unit tests waste money by making your agent generate more tokens and by adding useless CI runs Will report back soon with the results!
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A weekly RSI line of 32 would have missed Bitcoin's 2011 bear bottom. It reached 33.6 then. The next three lows were 25.8, 29.0 and 30.5, so the flash line is now 34.
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Three teams can own separate services and still wait on one release decision. That shared deploy path turns independent changes into one queue. Give each service its own deploy path so unrelated changes can ship on their own.
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Moinerus | Dev, AI, Crypto retweeted
Theory: Development teams are going away. We will increasingly work alone instead of on teams. Here’s why: Historically, writing software was slow, expensive, and required highly specialized knowledge about languages, libraries, and syntax. So, we grouped developers into teams to achieve sufficient velocity, and support specialization. Now, one dev can orchestrate multiple agents in loops to achieve an entire team’s output. No team required. Of course, lone professionals aren’t a new idea. Many industries often work alone. Doctors join a practice, but often see patents alone. Attorneys join a firm, but often try cases alone. Mechanics join a shop, but often service vehicles alone. Developers will soon be the same. We’ll join a company, but often build and manage entire apps alone. We’ll still interact with each other, but we will be more like doctors - we’ll advise and assist each other, but we won’t work together daily on the same code. Our new job is to create and manage “software factories” - agents that generate the software for us. You don’t need a team of devs to do that. So, software development isn’t dead. But the idea of multiple developers working on the same code is soon going away.
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The holder gap has one measured Bitcoin bottom: -0.124 in 2022. With no earlier trough to compare, that reading cannot tell us what a typical bottom looks like.
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Review the change when it's made. By release time, the checks have already run. A manual gate that rechecks the same evidence adds a queue, not a new control. What can that gate catch that the earlier checks cannot? If we cannot name it, improve the checks and remove the wait.
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Bitcoin's NUPL was negative at all four measured bear bottoms. The lows rose from -1.585 in 2011 to -0.326 in 2022. That shift makes one fixed bottom threshold a poor fit for the whole series.
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A frontend change can wait on a backend change, which waits on a tightly coupled microservice. Each team can finish its own work while the release still sits between them. Reduce those handoffs and the whole change gets through sooner.
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Bitcoin's 2025 MVRV Z top was 3.35. In 2013 it was 10.66. All four recorded tops stepped down. The bottoms moved up from -0.69 to -0.36. I wouldn't use one fixed MVRV Z threshold across those cycles.
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A wall of confusion can end in a manual release gate. Batches grow, releases become big bangs, and people get wary. Another gate goes in without making the release any smaller. The DevOps Handbook's First Way is about flow. I'd tackle the wall first.
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BTC cycle bottom: $40,600 to $50,700, 26 Sep to 31 Oct 2026. Low so far $58,525 and plenty reckon that was it. In which case I've missed the lot. My quant tool says lower. Quant's generous. Posting before the fact so it can be marked after. Egg on my face or a grin ;p
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Marking this on 1 Nov, the day after the window shuts. Hit or miss, it goes on the site next to the misses the method's already made.
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I may have been wrong still 1 month to go...
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A backlog ticket can outlive the facts it was written from. Check the current code and its dependencies, keep only the outcome we still need, then estimate that.
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Moinerus | Dev, AI, Crypto retweeted
People use Jev to pick a model before a task. I made it change GPT-6's reasoning effort inside Codex DURING the task. More thinking when stuck. Less for routine steps. 50% lower Astra costs in my tests. Faster runs, without breaking prompt caching.
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Couldn't get a TypeSafe key and wanted to play with Jev. I added a hidden Decisions route to Codex Router, backed by OpenRouter. Two small PRs later, jev-pruner can use the Router-held key. Jev stays out of the model picker. It is a Decisions model, not a chat model.
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Re-tested Jev with jev-pruner, rather than rewriting thread history. On noisy build output, it cut 253,391 chars to 99,660 in 959ms, kept the final test result and archived stdout/stderr exactly. It is useful output pruning. Native compaction still owns session memory.
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Wanted @tamarajtran's instant compaction dream to be true. Seeing Jev run at sub-second latency for fractions of a penny felt like magic. @theo posted his hot take against it, and I wanted him to be wrong. So I benchmarked it across real coding transcripts to see what the data says.
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Where does Jev actually fit? Not as a primary compaction engine for long tasks. But it shines for: - Pruning obvious stale read/build spam before a summariser - Low-stakes, cheap rerunnable utility loops - Real-time classification and routing where sub-second speed matters
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Verdict: Tamara built a neat, provocative experiment that forced everyone to look at compaction speed. Theo was right about the architectural failure mode of blind line-by-line filtering. You still need structured summaries and native context awareness for serious agent work.
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