Luke Jackson

1K posts

Luke Jackson

Luke Jackson

@m31uk3

2x Dad and Husband - (e/acc) - Current Work: Agentic Memory & Slop Detection.

San Francisco, CA Katılım Mart 2009
577 Takip Edilen110 Takipçiler
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Luke Jackson
Luke Jackson@m31uk3·
Exactly. Ineffective writing (derived by human or robot) “Recursively Tells” how “right” {x} is because of {y}: Da duh duh duh da duh. {repeat} Da duh duh duh da duh. {repeat} … Clear writing is clear thinking. Show don’t tell. … Effective writing “presents” chains-of-reasoning that allow the reader to connect the dots of the author’s argument (end-to-end) with minimal effort.
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Luke Jackson
Luke Jackson@m31uk3·
@iamdothash I often need to hyper concentrate on an LLM response. I use the Text-to-Speech feature of Mac OS X to have it read me the response while also reading it myself. This mitigates missing key details and improves my reading comprehension. I need to pause/play Cliamp in between.
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Luke Jackson
Luke Jackson@m31uk3·
@iamdothash sorry if I missed this, qq do you have your Cliamp setup to bind to the Mac keyboard buttons? Similar to how YouTube is able to do this even when the active page is in focus/visible?
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priyanshu.sol
priyanshu.sol@priyanshudotsol·
someone wrote a 680 page interactive book on cs algorithms
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Linghua Jin 🥥 🌴
Amazed by how fast the trends change over night - Codex @OpenAI all over the feed. You gotta win the community. @sama
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Mikhail Rogov
Mikhail Rogov@i_mika_el·
@LinghuaJ @OpenAI @sama codex just got better where claude code started to get worse and rip off customers. I experienced it myself, when my limits just dropped 2-3x
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Bjarne Øverli
Bjarne Øverli@iamdothash·
@m31uk3 @kepano That's really cool! Kind of hard to create a skin for something that does not support skins, though :D
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Luke Jackson
Luke Jackson@m31uk3·
@iamdothash How do we get @kepano to agree to help with a fire Cliamp skin? Do you think he likes butter tarts? His design career started at age 16, making pixel-art skins for Winamp. His skin "Impulse" for Winamp 5 was downloaded 100k+, one of the most popular skins ever!
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Leonard Nimoy
Leonard Nimoy@TheRealNimoy·
A life is like a garden. Perfect moments can be had, but not preserved, except in memory. LLAP
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Luke Jackson
Luke Jackson@m31uk3·
@code_kartik I’d build a different harness for a mobile surface than I would a desktop surface. Maybe I’m missing something and the harness is surface agnostic. 3 distinct harness archetypes though… maybe I’m right? -the claw/Hermes -the codex/Claude -the API wrapper/CoWork -the {mobile}?
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Luke Jackson
Luke Jackson@m31uk3·
@code_kartik What about the surface? What if we think bigger? Surface first thinking suggests we work backwards from a SME perspective who’s in the field or on the farm. I see no limiting factor which necessitates the HITL needs to be behind a keyboard and/or in an office.
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Luke Jackson
Luke Jackson@m31uk3·
Loved this piece. Right on point, scarily accurate for big tech rn. “They are organizations rebuilt around a new operating model.” Curious how much this is an operating model versus a culture? In my mind an operating model is what lives on paper, the culture, ethos, and soul of a company is what gets peer reinforced day-in day-out to delay “Day 2” as long as possible.
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Jeffrey Emanuel
Jeffrey Emanuel@doodlestein·
Jeffrey Emanuel@doodlestein

The bitter lesson applied to programming today is that you need to find ways to productively leverage as many tokens as possible. People roll their eyes at this concept because it's easy for this goal to be misapplied and lead to wasteful nonsense. But if you just think about it, it's obviously correct. The models are VERY smart now and can work basically 24/7 for you, and you can conjure up as many of them as you want. The only limitation is the number of Max/Pro accounts you have, and controlling enough fast machines with a lot of RAM and CPU cores to run them all. But that's just what you need to be in a position to do this. The bigger impediment for most is on the management side: how can you usefully direct and harness so many agents? And the answer is that you need to work towards the goal of removing yourself from the equation as the bottleneck for as many projects as possible so that you can be making real progress on them every day. This frees you up to focus your energy on the couple of things that are most critical for any given project and so you can do the planning and conceptual work on new projects without having everything else come to a halt. The solution to doing this in practice is to use the right tooling (like Agent Mail, beads_rust, bv, ntm, cass, dcg, rch, etc.), the right planning methodology (the complete Flywheel guide), and the right skills (from jeffreys-skills.md). Are there other ways to go about this? Sure, everyone is increasingly converging on the same basic principles. But I know for a fact that: * my tools (which are 100% free and open-source) really work (agent-flywheel.com/tldr); * my planning methodology and workflows really work (I've already used them to make extremely powerful ground-up software projects like asupersync and FrankenTUI; see agent-flywheel.com/complete-guide); * my skills enable a different level of autonomy and economy of expression (I've seen a huge inflection in my own output, which was already pretty crazy before, since I started using them universally in all my work). So that's why I recommend them to people. There are nearly 1,000 people in the Agent Flywheel Discord (discord.gg/gnCHsYDR25) now who can tell you the same thing: this approach really works, it's not just hype. I'm not trying to justify some crazy VC valuation. It's just me cranking away with my 52 AI subscriptions and giving 99% of it away for free. The only things I directly monetize are my skills, and they are just $20/month because I'm trying to prioritize growth (hey, it works for Netflix and Spotify!) So give it a try. If you already have Claude Max and/or GPT Pro, you have most of what you need to get started. You can run the tools on a mac, or better yet, rent a decent cloud server for $50 to $100/month, which works better and can scale more. The wizard on my agent-flywheel.com site walks you through every step of the process. I promise you that you won't regret taking the plunge. It's a lot to digest and understand and apply, but the rewards are magnificent right now because there's still huge alpha in being able to do this while 95%+ of the world thinks it's impossible or a pipe dream.

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Luke Jackson
Luke Jackson@m31uk3·
I feel like there’s a nuanced yet crucial dimension between what @pmarca is saying and this timeless Ray Kroc quote. "Nothing in the world can take the place of Persistence. Talent will not; nothing is more common than unsuccessful men with talent. Genius will not; unrewarded genius is almost a proverb. Education will not; the world is full of educated derelicts. Persistence and determination alone are omnipotent." He’s not saying you have to be a 0.001% talent nor is he saying hard work can somehow out perform genius. He’s saying that the pervasive trope of the business world for the past 50 years has been “business as usual” and that with globalization and the rise of agentic native systems “business as usual” is the antithesis of what you want/need running your company. No offense, but that is how Apple went from Steve Jobs to Tim Cook. It might work for Campbell’s soup, but it sure as shit didn’t work for ULA. x.com/GeniusGTX/stat…
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Luke Jackson
Luke Jackson@m31uk3·
As a daily Obsidian user since 2023, the milestones section with key feature highlights hit hard: • 2022: v1.0 launch + Canvas whiteboard + LYT/MOCs explosion. I’d used basic linking, but seeing how Canvas and Maps of Content fully replaced folders underscored the vault as a thinking space, not a file cabinet. • 2023: Properties launch. The visual editor for typed metadata (dates, checkboxes, numbers, links) replaced manual YAML. I’m a HUGE proponent of frontmatter for agentic search and memory — now I realize this wa a thoughtful feature by the obsidian team. (How do we make this a universal standard for markdown?) • 2024: Tab Stacking refinements + large-vault performance. I was unaware this was even a thing. I imagine my vault is around 7k files, I should check. I struggle daily with too many open notes and not being able to read the tabs. I’ll be learning how to use this “tab stacking” first thing Monday. IMHO, Taskade wrote a better Obsidian explainer than most Obsidian fans. Wild. Full article: taskade.com/blog/obsidian-… Which of this trivia / features did you just learn about today?
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Luke Jackson
Luke Jackson@m31uk3·
Idea. Create genuinely useful content that also happens to be the founding history of Obsidian (a competitor). taskade.com/blog/obsidian-… Then let it cook as organic SEO. @Taskade basically doing the “show, don’t tell” version of “our AI can curate better knowledge than anyone.”
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Luke Jackson
Luke Jackson@m31uk3·
"I make this random little thing, pixel art stuff, just for fun... but then hundreds of thousands of people download it and use it. It changes your perspective on what is the world actually."
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Luke Jackson
Luke Jackson@m31uk3·
Awesome! I had no idea this was a thing already! Exceptional common sense approach. Have you read the no-escape paper on the hard limits of RAG? CocoIndex feels like another key primitive we’ll need to solve agentic memory! —- CocoIndex is basically Change Data Capture (CDC) tailored for AI indexes and knowledge graphs. In traditional data engineering, CDC tools (like Debezium, Flink CDC, or Kafka Connect CDC) watch databases or files for changes (inserts, updates, deletes) and stream only the deltas so you don’t have to reprocess everything from scratch every time. CocoIndex does the same thing, but for messy, non-database sources that AI agents actually care about: •Code repos •Meeting notes / Google Drive / Notion •Slack / email •Any other unstructured or semi-structured data How it works (super similar to CDC): •Push-based CDC where available (e.g., Google Drive changelogs, Git webhooks). •Metadata-based change detection (file timestamps, Git history, etc.) for everything else. •Multi-level delta detection: it figures out exactly what changed at the component/function/target level. •Rust delta engine processes only the changes and applies minimal updates to your vector DB, graph DB, etc. (Pgvector, LanceDB, Neo4j, etc.). So instead of doing a full re-index every night (which is slow and expensive), it keeps everything continuously fresh with almost zero wasted work — just like a CDC pipeline, but purpose-built for RAG / LLM agents / real-time knowledge bases. That’s why their early traction is so strong: it solves the “my agent’s memory is always stale” problem that kills most production AI setups. If you’ve used CDC in ETL/ELT pipelines before, CocoIndex will feel very familiar — just with a declarative Python API on top and an AI-first mindset.
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Linghua Jin 🥥 🌴
This open source project is getting viral on linkedin ! - Your agents deserve fresh context. @cocoindex_io turns codebases, PDFs, Slack, inboxes, and videos into a continuously updated index your LLM app can actually reason over … no stale nightly batches, no context gap. Python on a Rust delta engine: edit a chunker or swap embedding models, only the affected rows re-run. Pgvector, LanceDB, Neo4j as targets. Byte-level lineage per row. Production agent ready in 10 minutes. Link to OP in comments!
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Aaron
Aaron@aaronp613·
Apple accidentally left Claude.md files in today's Apple Support app update (v5.13)
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