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[BrainHouse @IdeaRation]

@FemiJACOBS Every day is a gift; regardless of what comes and regardless of how things turn out; all things are working together for our good. And when the puzzle is complete and we see the big picture, we’ll look back and rejoice that what we thought was evil, was actually for our good.

[Curious Minds @CuriousMindsHub]

How to Become Well-Spoken:

[Francis Santora 🎌 @FrancisPSantora]

Short decks raise more money, not less.

Here's how to structure your deck...

1. Title
2. One sentence vision
3. Team
4. Traction
5. Market size
6. Competitors
7. Ask

[Peter H. Diamandis, MD @PeterDiamandis]

Let be clear: The best way to learn AI is NOT a course. It is building something real, pick a problem. Pick a tool. Ship something. You will learn more in 90 days of building than a year of reading.

[Millie Marconi @MillieMarconnni]

A journalist in 1987 rewrote the 2,500-year-old Tao Te Ching as a series of short parables about programmers, and the book became required reading inside Silicon Valley because every line of the joke turned out to be deadly serious.

His name was Geoffrey James.

He was not a famous engineer. He was a technology journalist who had spent years inside the offices of early software companies watching the same disasters play out over and over again.

Managers piling more programmers onto failing projects. Codebases collapsing under their own weight. Corporate hierarchies producing endless documents that nobody read. Geniuses being interrupted by meetings until they quit and went home.

He could have written a serious management book. Plenty of serious management books already existed and almost nobody in software was reading them. He decided to do something stranger.

He picked up a copy of the Tao Te Ching, the foundational text of Taoist philosophy written in China around 500 BC, and he rewrote it line by line as if Lao Tzu had been a master programmer.

The result was published in 1987 as The Tao of Programming. 151 pages. Nine books. Roughly 50 short parables. A comedy book on the surface and a philosophy book underneath, written in deliberately ornate language that made you smile while you were absorbing arguments that have aged better than almost anything else published about software in the last 40 years.

The opening line of the book is the giveaway. Thus spake the master programmer. When you have learned to snatch the error code from the trap frame, it will be time for you to leave. The joke is that he is parodying the kung fu master from the old Kung Fu TV show. The argument underneath the joke is that real mastery in software is not measured by what you can build. It is measured by how cleanly you can recover when the system fails.

The book has been passed around hacker communities continuously since the late 1980s. It sits alongside Fred Brooks's Mythical Man-Month on the required reading list of serious software teams. People who have never heard of Geoffrey James still quote his lines without knowing where they came from. The reason it has refused to die for 40 years is that every line of the parody was always disguising a piece of real wisdom that nobody else was willing to say plainly.

Here are some of the lines, and what each one is actually saying.

"Even a perfect program still has bugs."

The line is funny because it sounds like a contradiction. The truth underneath is that there is no such thing as a finished program. Every system you ship is alive. It is going to encounter inputs you did not anticipate, hardware you did not test on, and edge cases your imagination could not produce.

Treating any piece of software as finished is the single most common reason production systems fail. The masters in the book are calm about bugs because they have stopped pretending bugs are exceptions. Bugs are the default state. The programmer's job is to keep them from compounding.

"Let the programmers be many and the managers few. Then all will be productive."

The line is funny because every software company in the world does the opposite. The truth underneath is that programming is a kind of work that runs almost entirely on uninterrupted thought, and the more layers of management you stack on top of it, the more interruptions you create, the more meetings the programmers have to attend, the fewer actual hours of deep work get done.

Every manager you add to a software team subtracts more productive hours from the engineers than the manager could possibly add through coordination. Brooks proved this formally in 1975. James said it in nine words in 1987.

"After three days without programming, life becomes meaningless."

The line is funny because it sounds like an addict talking. The truth underneath is that genuine craft work produces a kind of meaning that almost nothing else in modern life provides. The programmer who has not touched real code in three days is not just bored.

They are emotionally underfed. The masters in the book understand that the work itself is not a means to a paycheck. The work is the reward. The paycheck is a side effect. Everything that interferes with the actual work, no matter how prestigious or well-paid it looks, is making the programmer's life worse, not better.

"A manager went to the master programmer and showed him the requirements document for a new application. The manager asked the master, how long will it take to design this system if I assign five programmers to it? The master replied, it will take one year. The manager said, but we need this system immediately or even sooner. How long will it take if I assign ten programmers to it? The master programmer frowned. In that case it will take two years."

The line is the punchline of Brooks's Law disguised as a koan. Adding programmers to a late project makes it later, because every new person has to be brought up to speed by the existing team, which slows the existing team down, which extends the timeline. The book teaches this in 60 words. The same lesson takes most managers 20 years of failed projects to learn, if they ever learn it at all.

The deeper pattern is the one most readers miss the first time through.

James was not really writing about programming. He was using programming as a setting for a much older argument that Taoist philosophy has been making for 2,500 years.

The argument is that the world is governed by simple principles that get harder to see the more cleverness you stack on top of them. Force does not work. Pressure does not work. More resources do not work. The only thing that works is restraint, simplicity, and the patience to let the right shape emerge.

Lao Tzu was talking about how to govern a kingdom. James was talking about how to ship software. The wisdom is the same. The kingdom is the codebase. The emperor is the project manager. The advisors are the developers. And the entire collapse of every doomed software project in the last 40 years has had the same root cause that the collapse of every doomed dynasty has had for the previous 4,000.

People mistook complexity for competence.

The book has been sitting on the internet for free for almost 30 years. You can read all 151 pages in an afternoon. Most people who run it as a joke walk away quoting it for the rest of their careers.

What James understood in 1987 is even more true in 2026. AI can now generate millions of lines of code in seconds. The bottleneck has shifted entirely. The bottleneck is no longer typing speed. The bottleneck is judgment. The bottleneck is taste. The bottleneck is the ability to look at a generated codebase and feel, without quite knowing why, that something is wrong with it. That kind of feel is exactly what the book was teaching all along.

The Tao of Programming flows far away and returns on the wind of morning.

The masters in the book were never joking. The world just took 40 years to figure out they were not.

[liminal @Liminal1988]

and whatever you choose in life,

[Martin Tobias (Pre-Seed VC) @MartinGTobias]

The best founders solve problems they've lived.

Not problems they've read about.

[1752vc @1752vc]

15 Idea Stage Investors

@HarpoonVentures — $100k–$5M Early-stage investor focused on national security technologies

@1752vc — $100k Invests in early-stage tech

Julian Capital — $750k Deeptech seed fund

@AntlerGlobal — $125k Invests at day zero, pre-idea/pre-team

@BlackFlagVC — $100k–$1M Invests in early-stage tech and high-growth startups

@FirstMileVC — $100k Invests in early-stage tech and AI startups

@outsetcap — $200k–$400k Backs early-stage startups building innovative technology solutions

@redbudvc — $50k–$150k Early-stage tech investor

@SusaVentures — $1M–$2M Focused on data-centric, moat-driven startups

@1517fund — $50k–$400k Provides R&D checks for technical founders

@1UpFund — $500k Invests in gaming and VR startups

@500GlobalVC — $100k–$5M Focused on fintech and AI

@7wireventures — $100k–$5M Invests in healthcare startups

@8bitcapital — $100k–$1M Focused on software tools with network effects

@VenturesAv8 — $500k–$10M Backing early-stage healthcare startups powered by AI

@axialvc — $100k–$5M Invests in early-stage life sciences companies

[Fathers Diary @Fathers_Diary]

A man without boundaries get used by everyone.

A man without purpose is led by anything.

A man who doesn't study says anything.

A man without limits does anything.

Be a man with boundaries, purpose, knowledge and have limits, you'll go far in life.

[Leaders 𝕏 Junction @LeadersJunction]

Treat your energy like money. Spend it only on people and places that give returns.

[𝐓𝐡𝐞 𝐏𝐫𝐞𝐬𝐞𝐫𝐯𝐞𝐫 @ThePreserverofU]

THE GAME OF WEALTH

LEVEL 1
1) Kill bad debt
2) Create a budget
3) Gain complete focus
4) Build emergency fund
5) Learn financial basics
6) Avoid impulsive spending

LEVEL 2
1) Find your passion
2) Work your ass off
3) Sacrifice fun
4) Build skills
5) Network smartly
6) Stay consistent

LEVEL 3
1) Save, save, save
2) Minimize spending
3) Value your money
4) Automate savings
5) Diversify savings
6) Track net worth

LEVEL 4
1) Invest savings
2) Start businesses
3) Create multiple income streams
4) Learn investing
5) Build assets
6) Teach others

Wealth is a game of levels.

Master each stage, stay disciplined, and financial freedom becomes inevitable.

[𝐓𝐡𝐞 𝐏𝐫𝐞𝐬𝐞𝐫𝐯𝐞𝐫 @ThePreserverofU]

WHEN LIFE WANTS TO TEACH YOU SOMETHING

1. It makes you lose money in the same pattern.
2. It removes people you thought were permanent.
3. It repeats the same painful situation again and again.
4. It brings the same type of toxic relationships.
5. It creates obstacles that force you to grow.
6. It breaks your ego when you refuse to change.
7. It gives you the same lesson in different forms.

Life will keep repeating the same situations, pain, and struggles until you finally learn the lesson.

To learn it, otherwise it will repeat until you learn it.

[Ken 🧙 @thekenndubisi]

If you are a vibecoder in Nigeria and you are very good at creating vibecoded websites with Claude, Lovable, etc and you also know how to host them, let me know how much you charge to deliver a website.

I’ll bring the work to you at your price.

If possible send links to the sites you’ve built that are live.

[Andrew Ng @AndrewYNg]

One of the new, buzzy jobs in Silicon Valley is the AI Forward Deployed Engineer (FDE), an engineer who is embedded within a client organization to help customize solutions, such as building and tuning agentic workflows that suit the client’s particular needs. I’ve heard from people who are wondering anew about the FDE career path since OpenAI and Anthropic started building new teams to place FDEs within client organizations.

The rise of FDEs for AI workloads is one way AI is creating new jobs (and why the jobpolcalypse narrative of upcoming job market collapse is false -- there will be many AI and non-AI jobs). However, I believe there will be far more AI Engineer jobs than FDEs, as I explain below.

The FDE role was pioneered about two decades ago by Palantir, which sent engineers to government locations to work on secure, air-gapped networks. In addition to having good technical skills, FDEs need communication skills and sometimes business skills. For example, they may need to speak with clients to understand their needs, formulate a strategy to prioritize projects, explain complex technology, and respectfully push back if a client asks for something unrealistic. They’re enjoying a resurgence because of the amount of work involved in taking an off-the-shelf LLM and building it into a custom agentic workflow that fits particular business needs.

However, I believe the number of AI Engineer jobs will be far larger. A company might accept a few FDEs to be embedded within its organization. But most companies will want far more of their own employees working on their projects. While my organizations do hire FDEs, we hire far more AI Engineers! Also, a common client concern is that it is hard to find vendor-neutral FDEs — they are, after all, there to deeply integrate a particular vendor’s product into a company. In this moment when it’s hard to predict which AI service will be the best one in a year’s time, optionality (the ability to pick whatever vendor turns out to fit best in the future) is very valuable. In contrast, letting FDEs tightly bind a company’s processes significantly reduces optionality.

Right now, I see surging demand for AI Engineers who can build software applications using AI software components (like LLM prompting, agentic frameworks, evals, etc.) and effectively use AI coding agents (like Claude Code, Codex, Antigravity CLI, and OpenCode). As the AI Engineer role matures, I expect it to fragment into more specialized roles, like the generic Software Engineer role from decades ago fragmented into frontend, backend, mobile, data engineering, devops, and so on.

What will be the future, specialized AI engineering roles? I don’t know. Perhaps there will be AI FDEs, LLMOps Engineers, Evals Engineers, AI Data Engineers, Harness Engineers, and other roles we don’t have names for yet. But for now, I see a lot of AI engineers who are generalists create a lot of value. Skilled AI Engineers are in very high demand! As our field continues to mature over the coming decade, I look forward to new specializations within AI Engineering that create even more job opportunities.

[Original text: The Batch newsletter]

[Codie Sanchez @Codie_Sanchez]

You should spend 10x more time thinking about your customers than your competitors.

[Robert Greene @RobertGreene]

If you work on yourself first, developing a solid work ethic and organizational skills, eventually the right teacher will appear in your life.

[Mark Manson @Markmanson]

You don’t find your purpose. You build it, brick by brick, mistake by mistake.

[Okara @askOkara]

how to build a content engine without hiring writers:

> go to https://t.co/8b7IyKw1Uj
> drop your website url
> connect google search console
> it finds queries getting impressions but no clicks, low-ranking pages, missing keyword opportunities, topics your competitors rank for that you don't
> it writes articles around those opportunities and auto-publishes them to your cms every day

[Eunice Ajim @euniceajim]

Only take advice from people who are actually doing what you want to do, not those who are simply projecting their own reality onto your ambitions

[Arti Shah @TechByArti]

🚨BREAKING: Claude can now teach you any skill in 30 days for free.

Use these prompts to replace $20,000 courses and 4-year degrees:

[Douglas Loveday @DouglasLoveful]

If you want to win long-term, pay attention to these 5 buckets:

1. What you know (your knowledge)
2. What you can do (your skills)
3. Who you know (your network)
4. What you have (your resources)
5. What the world thinks of you (your reputation)

Invest in all five. They compound over time.