gildoron

[gildoron @gildoron]

@FreddyLA7 Steiner ranch steakhouse?

[sim @simscircuit]

Did not expect a question that starts out 'Do you think before you speak?' to go so well. A+ question from Charlotte Harpur A++ response from Eileen Gu.

[CNN @CNN]

The US military has developed new strike plans that include potentially using the so-called "mother of all bombs" to target Iranian energy infrastructure and nuclear sites should President Donald Trump give the order to resume combat operations either before or after the midterm elections, according to multiple US officials familiar with the matter. https://t.co/AXQL6sYxVn

[gildoron @gildoron]

@AmyPJohnson Thanks!

[gildoron @gildoron]

Silicon Valley built the software era. Texas could help build the autonomous warfare era.

Defense tech brings together AI, advanced manufacturing, robotics, and national security.

The next generation of tech giants may build machines, not apps.

[gildoron @gildoron]

Silicon Valley built the software era. Texas could help build the autonomous warfare era.

Defense tech brings together AI, advanced manufacturing, robotics, and national security.

The next generation of tech giants may build machines, not apps.

[gildoron @gildoron]

@theSnatchedPod 💪

[gildoron @gildoron]

Saving this. Thank you.

[GREG ISENBERG @gregisenberg]

I spent 48 hours in SF hanging out with billionaires, data labs and AI founders and execs running $1B to $100B companies.

My observations:

1. Sooo MANY stories of data brokers making like $2M a WEEK selling company data to labs. I can't tell if it's the beginning or a bubble, and I kept wondering which niches are left. Digging into it actively.

2. At dinner, someone asked the table, "If a new model drops next month, does your company get better or worse?" HALF the table went quiet! I think that's the best question to ask about any AI startup right now.

3. The bar people talk about now is hitting $1B in revenue in 12 months (I guess that's the new unicorn?). What I didn't hear much about is retention. AI revenue can come in fast and leave fast, and I think we're going to see a lot of stories of AI companies with huge revenue and terrible retention.

4. It's pretty clear we're living through the reinvention of the computer. The model is the CPU, the harness is the operating system, and skills and plugins are the apps. Thinking about it that way makes it easier to see where the whitespace is.

5. We're maybe 12 months from an agent that can watch you work for a week and then do your job without any instructions. The screen recording plus agent memory plus local model combination makes this possible right now.

6. Agent harnesses feel like the new GPT wrappers, in a good way, especially vertical ones. The best teams I talked to treat the model as swappable. One founder walked me through routing different models to different jobs: one for taste and visuals, a cheaper one for the everyday stuff, another for text.

They use prompts they can move across models over fine-tuning, and A/B test the output on what users actually do with it: do they edit it, export it, share it? A vertical harness is basically four things: the connectors for that industry's data, evals written by people who know the work, rules for what the agent can and can't touch, and a clean screen for a human to review. The model is maybe 20% of it.

7. There's a lot of reverse engineering going on/cloning going on more than I've ever seen. People are decompiling software and rebuilding it with agents, and someone showed a suite of like 10 apps that are worth $5B+ each all that he cloned open source. Me and everyone are still thinking through what it means when software gets this easy to copy.

8. My guess is the value moves to data. If the software can be rebuilt quickly, what's worth paying for in a legacy SaaS company is the years of customer data and workflows inside it. Some SaaS companies are secretly data companies.

Gets me thinking about how do you truly value data for this saas companies? Like if we were buying these dying saas companies at 2x ARR before (as example), maybe there is a better metric. Idk, just thinking out loud here.

9. It feels like a good chunk of legacy software won't make it to the agentic era, especially anything built around people clicking through a lot of screens.

10. Every company I talked to wants to pipe its internal data into one place and expose it to agents through MCP. Then they look at the data and realize it's a mess: five versions of the same customer, old Slack channels, PDFs nobody can search. Cleaning that up feels like a big consulting opportunity!

11. A lot of founders are building the basic building blocks for agents: APIs, data layers and tools. Some of the companies I saw barely have a UI because the main user is an agent. I really believe the startups that build primitives to this agentic era will do extremely well. Building blocks is the best way to think about it.

12. Labs can get plenty of training data, but it's harder to get real examples of agents failing inside companies. Whoever has those logs has something valuable.

13. Someone running a big consumer company told me the next fight is over memory. The model that remembers the most about you wins, and the smartest model matters less than people think.

14. Physical AI came up a lot. Astra I think was the first model that got people into AI can actually do CAD, and I think a lot of people are thinking what does vibe manufacturing really look like. The line I keep thinking about came from a robotics founder: the hardest problems in AI are deployment problems now, not research problems. Their robots work on their own, call a human when they get stuck, and every one of those calls becomes training data.

15. Cybersecurity companies are having a moment and are actually cool companies to build now, especially the ones that clean up after a breach. Every agent with access to your systems is a new door into your company, and a lot of those doors were left open.

16. Some startups are worth more dead than alive now. A shutdown company with 5 years of Slack, email and code can get paid for licensing all of it. I wouldn't be surprised if founders start factoring that into when they shut down.

17. People are starting to talk about monetizing the agent web. It feels really early, but when the most popular user of the internet is an agent, what startups should you be building?

18. I think agent insurance is coming. Once an agent makes an expensive mistake, insurers will want audits before they cover anyone.

19. Several people said the hire they want most is someone with taste who can write evals. The models are getting good at generating ideas, so the hard part is judging which ones are good.

20. New trend I observed: startup raises VC, uses venture dollars to become a creator, startup fails, founder falls back on being a full-time creator and incubates other products bootstrapped.

21. Getting SIGNIFICANT distribution is HARD right now. Founders are sponsoring buses, buying billboards like crazy and throwing parties with famous DJs to get noticed. Kinda feels dotcom era in that sense.

Attention is what's scarce! The growth guy going viral sharing his UGC strategy from Wispr Flow is a good example. It's the sauce everyone wants, and I truly believe there are probably only 50 people on the planet who know how to scale these types of businesses efficiently in this era.

Always good to get that dose of SF. I felt sooo lucky to have such an incredible trip during such an incredible time in building businesses. Surreal in so many ways.

Happy to be home and locked in.

Until next time!

[gildoron @gildoron]

@theSnatchedPod Agree. And the city is just getting better by the day

[jack @jack]

excellent

[Alex Finn @AlexFinn]

Local AI is the future, and if you’re not on the bandwagon yet then you’re delusional

A 27B model just released today that can run on your iPhone

Based on Qwen 3.6 Which is Sonnet from 6 months ago level, PrismML figured out a way to fit it on a mobile device

Is it the smartest AI model ever? No.

Is it the fastest AI model ever? No.

Will it be your daily driver? Not even remotely close.

It probably won’t even take away most major workflows for you.

But here’s the point: look at the trajectory. Look at where we were 6 months ago, 12 months ago, 24 months ago

24 months ago local models were for massive multi million dollar data centers

Now you can fit them on your phone

If you don’t think 12 months from now we’ll have models better than the ones out today running on Mac Minis, you just have 0 foresight

Start educating yourself on local AI now before it eats everything

[witcheer @witcheer]

few days ago I asked how you run Hermes.

250+ replies came back: 70 of you gave real answers and 60 described full setups.

I read and hand-tallied every one. here is what this community runs, in six numbers. 🧵

[Alex Finn @AlexFinn]

I did it. I figured out the perfect AI coding loop

It's called the Finn Loop and it's 100x'd my vibe code output while cutting the work I need to do down by 95%

ANYONE can implement this. It's super easy. Here's how it works:

1. 3 new skills inside your coding agent. /spec, /build, /review

2. You start out with /spec "your idea". The skill then asks you enough questions to fully understand your idea in detail then create a detailed spec inside Linear (amazing project management tool. Very generous free tier)

3. In another Codex/Claude Code session: you have a /build loop running. Once a spec is created, the /build skill picks it up and builds it out for you. Then advances the status of the issue in Linear

4. In another session, you have /review loop running. It picks up every issue that is built out then reviews it. Checks for security issues, optimization issues, then tests the code in its own browser, lays out test steps, takes screenshots, creates a PR, and puts it in its own vercel test sandbox for you to test it

5. The review loop then takes all of that and pings you in a channel in your favorite messaging service. I use Slack for this. It shows you the PR, gives you all the testing steps, and executive summary of the changes, and a link to the Vercel sandbox where you can test it

6. You go to the message in Slack, review the change, then send a rocket ship emoji as a reaction. This signals to the loop that the PR should be merged.

The only manual steps in this loop are you submitting an idea to your agent, and verifying the change at the end. Everything in between is automated in the loop.

Your vibe coding workflow today is hand holding your agent step by step on everything you build. You spend all day doing this.

Your vibe coding workflow when using the Finn Loop is you wake up, make a cup of coffee, give your agent a list of ideas, then come back at night and review all the changes. You're free to do whatever you want during the day.

Let me know if you want my full spec, build, and review skills. Will release them soon. Will also film a tutorial video on this.

There's also a ton more details I'll share shortly too, like the interface I built for monitoring all of this.

You also can probably just send this tweet to your agent and it will recreate the Finn loop for you.

Carve off some time and try this out today. I promise it will dramatically improve your workflow

[Josh Chambers @JoshChambers]

Alright 🔥 I'm watching this @TomBrady clip on overcoming self-defeating attitudes and taking ownership of your situation every morning after I wake up this week to get juiced 🔋 up:

Do the best with what you've got, not with what you wish you had.

The moment you stop blaming circumstance, is the moment you start getting better. 📈

Energy, attitude, and effort are choices. Ownership is the foundation they all rest on. 💪

[Jamon @jamonholmgren]

I'm just going to dump my whole agentic setup out here, because I see too many people missing giant chunks of this and it's hurting them.

Here's what I have and recommend:

0. an AGENTS.md that is a router -- it sends the agent to the right skills, docs, tools

1. a standard workflow doc/skill customized to my needs ... (grab Matt Pocock skills if you don't already have something) ... I tag this in most sessions with `@/AGENT_WORKFLOW.md` and it pulls it in.

2. self-healing docs for every system, and agents are instructed to keep them updated ... I tag the ones I know I need, or let the agent find them through AGENTS.md ... I also provide a more detailed summary in the first 7 lines of every doc, so they're easily greppable to find the right thing, and this is documented in AGENTS.md

3. agents always run the app ... the agent should always actually run the app itself, and test its work and fix issues as it goes, especially if running autonomously / asynchronously

4. end-to-end tests and instructions to write more and keep up to date, and docs on how to write tests, what to avoid, and a list of all the tests and what they test in yet another markdown doc ... write and run targeted tests during implementation, improve and commit with work

5. custom linters at precommit hooks looking for any problems you run across, with `--fix` fixing the problems automatically, OR if that's not feasible, it shells out to a cheaper LLM like Composer 2.5 or Sonnet to fix the problems -- NOT just flagging them, but actually resulting in cleaned code

6. cross-agent review at each major point: research, plan, implementation, and wrap-up. I mean codex, claude, cursor, whatever -- but it shouldn't be the same model reviewing the same code. And specific docs for agent review, what to look for, how to approach it. Also, personas -- looking at the code from different perspectives, such as maintainability, code quality, security, performance, AI smells, domains (e.g. "financial services expert" or whatever) ... and each persona also "owns" a set of system docs too and keeps them up to date

7. agent traces / worksheets that track what the agent is doing each session. if the agent fails partway through, you should be able to hand this worksheet to another agent and it could finish the job. commit this worksheet with the work so it's all connected and easy to reference later (you will reference these later!!), also have the agent apply git tags that correspond to specific worksheet names so they're easy to find

8. automatic agent feedback to you at the end of the session, added to a doc that is also committed with the work, that you periodically ingest into an interactive session and improve your workflows

9. a tools or bin folder that contains python or bash scripts that the agent has skills to make to make its job easier (for example, I have an `agent_review` bash script that lets the agent kick off agent reviews via CLI without knowing each agent's particular incantations) ... docs on how to make scripts effectively, and instructions to constantly build these out more

10. periodic agent sweeps through recent commits, looking for problems / gotchas from a higher level across commits

11. a coding conventions doc that is just for specific coding conventions you want to see in the code base, your review agents use these a lot (but a lot of this should be in linters)

12. an agent loop / night shift skill for autonomous work, that lays out how the agent is to approach this, from an orchestration standpoint

13. a task queue that is accessible to the agent (mine is just a TODOS.md, but yours might be in Linear etc, with a CLI to fetch via API)

14. a periodic false-confidence test audit skill that looks for tests that aren't actually testing what you think they're testing, and that fix those

15. visual regression tests -- take screenshots, compare via tool and with agent visual review, commit with work (git lfs useful here) or at least push into the PR

16. automatic performance benchmark tests that notice when performance degrades

17. performance profiling tools that can be used by agents for targeted benchmarking, trying new techniques, comparing outputs, and comparing profiles

18. end-of-shift full validations, including running all tests, performance, agent reviews, sweeps, everything -- when you return, it's all as pristine as it can be

If you have all this, your agentic coding experience is going to be very different than dry prompting and manually guiding it toward the right thing every time.

[Charlie Hills @charliejhills]

I turned Claude into an entire company.

42 skills, organised like a real org chart (links below):

Here is every department, and where to get each one.

Developers

Superpowers

→https://t.co/tGNwFVYsEa

Context7

→ https://t.co/oExBVynS4S

Skill Creator

→ https://t.co/iR9fyxUFvL

MCP Builder

→ https://t.co/iR9fyxUFvL

Webapp Testing

→ https://t.co/iR9fyxUFvL

Claude-Mem

→ https://t.co/emHpdPtiUO

Designers

UI UX Pro Max

→ https://t.co/54NvwKmBix

Taste

→https://t.co/gFud3Sa93j

Frontend Design

→ https://t.co/gFud3Sa93j

Transitions

→ https://t.co/kZP238n3Zy

Web Artifacts

→https://t.co/iR9fyxUFvL

Brand Guidelines

→ https://t.co/iR9fyxUFvL

Marketing

45 skills to run your marketing, from copywriting to SEO to lead magnets.

Access them all here

→ https://t.co/oBsac9TKK4

Social Media

17 skills to run your social media, from post writing to Reels to thumbnails.

Access them all here

→ https://t.co/ZwNtoUTdVm

Finance

8 skills to run your finances, from statements to reconciliation to audits.

Access them all here

→ https://t.co/qk0ioMAxim

Small Business

31 skills to run your small business, from cash flow to payroll to invoicing.

Access them all here

→ https://t.co/m9kHptmfv9

Legal

9 skills to handle your legal work, from contract review to NDAs to compliance.

Access them all here

→https://t.co/ucxqTYH4v9

Every skill on the chart is real and installable from the links above.

Repost ♻️ this to help your network build their own.

[Tim Ferriss @tferriss]

There is a process that I have used, and still use, to reignite life...

Create two timelines—6 months and 12 months—and list up to five things you dream of having (including, but not limited to, material wants: house, car, clothing, etc.), being (be a great cook, be fluent in Chinese, etc.), and doing (visiting Thailand, tracing your roots overseas, racing ostriches, etc.) in that order.

If you have difficulty identifying what you want in some categories, as most will, consider what you hate or fear in each and write down the opposite.

Do not limit yourself, and do not concern yourself with how these things will be accomplished. For now, it’s unimportant. This is an exercise in reversing repression.

Be sure not to judge or fool yourself. If you really want a Ferrari, don’t put down solving world hunger out of guilt. For some, the dream will be fame, for others fortune or prestige. All people have their vices and insecurities. If something will improve your feeling of self-worth, put it down.

Drawing a blank? In that case, consider these questions:

1) What would you do, day to day, if you had $100 million in the bank?
2) What would make you most excited to wake up in the morning to another day?

Don’t rush—think about it for a few minutes.

If still blocked, fill in the five “doing” spots with the following:

— one place to visit
— one thing to do before you die (a memory of a lifetime)
— one thing to do daily
— one thing to do weekly
— one thing you’ve always wanted to learn

What does “being” entail doing?

Convert each “being” into a “doing” to make it actionable. Identify an action that would characterize this state of being or a task that would mean you had achieved it. People find it easier to brainstorm “being” first, but this column is just a temporary holding spot for “doing” actions.

Here are a few examples:

1) Great cook —> make Christmas dinner without help

2) Fluent in Chinese —> have a five-minute conversation with a Chinese co-worker

Determine three steps for each of the dreams in just the 6-month timeline and take the first step now.

Define three steps for each dream that will get you closer to its actualization.

Set actions—simple, well-defined actions—for now, tomorrow (complete before 11 A.M.) and the day after (again completed before 11 A.M.). Once you have three steps for each of the four goals, complete the three actions in the “now” column.

Do it now. Each should be simple enough to do in five minutes or less. If not, rachet it down. If it’s the middle of the night and you can’t call someone, do something else now, such as send an e-mail, and set the call for first thing tomorrow.

If the next stage is some form of research, get in touch with someone who knows the answer instead of spending too much time in books or online, which can turn into paralysis by analysis.

The best first step, the one I recommend, is finding someone who’s done it and ask for advice on how to do the same.

[GREG ISENBERG @gregisenberg]

Grok 4.5 might be the BEST model to run inside Hermes or OpenClaw RIGHT NOW.

I've been sleeping on Grok to be honestNot anymore.

It's more than 60% cheaper than Opus 4.8 and lands around $2.49 per task versus ~$12 for Fable in Claude Code. And it's fast.

So what happens when you give Hermes + Grok 4.5 its own email, its own phone number, its own debit card, and access to every tool you use?

You pretty much get an AI co-founder.

Everything you need to know about Grok 4.5 + Hermes below.

Full episode is available to watch at @startupideaspod ( thanks @nickvasilescu for coming on)

I slept on Grok. Not sleeping on it anymore.

Watch

[Marc Andreessen 🇺🇸 @pmarca]

Interesting.

[Aparna Dhinakaran @aparnadhinak]

https://t.co/31rd1aRZNM