Anthony Diké

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Anthony Diké

Anthony Diké

@antdke

professional token shuffler

New York, NY Katılım Temmuz 2017
677 Takip Edilen1.9K Takipçiler
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Anthony Diké
Anthony Diké@antdke·
⚡40 pro tips for writing great microcopy THREAD...
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Anthony Diké
Anthony Diké@antdke·
Software engineering in June 2026: 1. Design loop 2. Execute loop 3. Walk away from computer (Optional)
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Anthony Diké
Anthony Diké@antdke·
@hiiinternet Great writeup Seb! I was tempted to do something similar myself for my own knowledge. Thanks for spending the tokens 🫡
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Anthony Diké
Anthony Diké@antdke·
@packyM @markiewagner Great piece, Packy. One funny idea that emerged from this: What if you couldn’t start an agent process unless you had a goal? Like, the harness would just prevent you from spending tokens unnecessarily unless you had a clear business goal that was relevant to the company.
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Packy McCormick
Packy McCormick@packyM·
In November 2022, @markiewagner wrote Choose Good Quests, then she went dark to work on her own. Today, she's launching Poetic, a new class of software that's adaptive like AI, reliable like code. This is her first public essay since CGQ, on why & how. notboring.co/p/return-on-to…
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Anthony Diké
Anthony Diké@antdke·
"If the work can't be scored from outside, someone on the inside has to decide what a good answer even is, and that decision is the whole game." Great read. Confirms a belief I've held lately - the key to implementing custom AI agents and workflows for companies is that the outputs must be verified by the domain expert(s) inside the organization. You can have them do that manually or, if possible, automatically with their taste and judgement encoded into skill files.
sarah guo@saranormous

x.com/i/article/2064…

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Anthony Diké retweetledi
Sam Stoffel
Sam Stoffel@sam_stoffel·
I come back to this speech every once in a while: “in the 1,526 singles matches I played in my career, I won almost 80% of those matches … what percentage of points do you think I won in those matches? only 54%.”
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Anthony Diké
Anthony Diké@antdke·
@rohitdotmittal i like this framing it's like a "book-of-business" roll up they're buying the team + earned trust from the sale to acquire the logo
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Rohit Mittal
Rohit Mittal@rohitdotmittal·
Fast growing companies only buy 2 things: - talent - logos (big logos) This is Legora's 4th acquisition this year - in 5 months. It's the clearest exhibit yet of a pattern I see play out at this stage. The best way to get a strategic exit is to have big-name logos in a hot industry - even if you have $1M ARR. This could be a better outcome than building a $3M ARR business without big logos. VCs or other buyers are not interested in a small outcome, but companies flush with cash and equity would love to buy you. When they add logos (not the revenue), they can cross-sell their bigger platform at a higher ACV. The same revenue and the same logos are worth far more under their roof than under yours. As the power law becomes more extreme (favoring incumbents and bigger players), if you are not one of the top 3 players, you'd either be gobbled up or wouldn't find capital to reach the next stage. How these deals generally work: - if you've raised seed (~$5M-$10M), investors usually get most or all of the cash - founders get healthy retention packages - good salary, plus equity in the acquirer - the team gets jobs at the same level (sometimes with slightly better pay and a little equity) You become a new line of business inside the acquirer. Think of it as somewhere between an acqui-hire and a real acquisition. And these only get done by founders, not bankers. They're strategic-fit conversations, not financial multiple negotiations - a banker's process kills the deal before it gets to terms. The momentum of these deals has increased as the top player pulls away from the pack at a fast rate. And it's going to get faster.
Max Junestrand@MaxJunestrand

Today, I'm excited to announce that @WeAreLegora has acquired Cadastral. Cadastral is an AI agent platform built specifically for commercial real estate, trusted by JLL, AvalonBay, Equity Residential, and Empire State Realty Trust. In just over a year, they've signed 50+ firms and grown revenues by 40% per month on average. Why CRE? Because it may be the most legally intensive industry on earth. Acquisitions. Leases. Refinancings. Disputes. Every deal produces a wall of documents that demands precision. Legal teams here have never had AI built for them, until Cadastral. Co-founders Abe Somani and Aman Dhesi and their NYC engineering team are joining Legora, and planting the flag for our first major US engineering hub. We're building toward 200+ people in New York and 300+ across North America by end of 2026. This is our fourth acquisition this year. The thesis is consistent: Legora is an agentic operating system for legal work wherever that work happens. Law firms. In-house teams. And now the industries that create the most complex legal work in the world. CRE is next. It won't be the last. Welcome, Abe, Aman, and the Cadastral team. Full story: legora.com/newsroom/legor…

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Anthony Diké
Anthony Diké@antdke·
@bhalligan skill issue you could be doing a back-and-forth with the agent to understand what: 1) current state 2) the end goal 3) options and tradeoffs at each step you need to be in control and steering the model serves you. up to you to be learning while building
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Brian Halligan
Brian Halligan@bhalligan·
When your engineer finishes a session with a coding agent, they have more code than they started with and exactly the same amount of skill. The agent produced output. It did not produce understanding. You paid frontier prices to make your codebase bigger and your engineer no smarter. That is not an accident. It is a design choice, and it is worth remebering who it serves.
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Peter Hague
Peter Hague@peterrhague·
If anybody is wondering if the Jevons Paradox applies to AI, today I typed “git status” into Claude Opus because I couldn’t be bothered to open another terminal.
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Anthony Diké
Anthony Diké@antdke·
This is so true. Going forward, every company needs some form of a “data warehouse”. Something that ingests, organizes, and houses all their structured and unstructured data. First job of a good AI consultant is creating that and instilling a data/context extraction practice at the company.
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Mike Fishbein
Mike Fishbein@mfishbein·
After 40+ forward deployed engineering (FDE) engagements, we learned the hardest part of building AI agents and tools is Context Extraction. FDE sounds like an engineering role. It's actually 3 jobs in one: • Consulting - where in the business to build • Product - what to build • Engineering - how to build Coding is the easy part now thanks to Claude Code, @cursor_ai, and other coding agents. The hard part is everything before the code. Extracting context from clients who have it scattered across people and tools. And creating context when it doesn't exist at all. Then using that context to figure out what to build, and work with AI on architecture and development plans. FDEs turn the chaos and unknowns within every company into shipped AI applications. That's why every major AI company is building an FDE arm. OpenAI and Anthropic recently raised $5.5B for theirs. Cursor and others have several open FDE job listings. But their returns won't come from service revenue. They'll come from tokens and subscriptions. Service revenue doesn't matter to VCs, only tech revenue does because it's more scalable. Here's how FDEs make coding agent companies trillion dollar companies: Cursor and Claude Code are currently focused primarily on the professional engineer market. But the total addressable market (TAM) for coding agents is infinite because almost every job benefits from code. It just used to be too expensive. FDEs are the bridge from the technical market to the non-technical market, which is far larger. Every coding agent and LLM company will eventually automate and productize their FDE teams though. So we decided to replace ourselves before someone else does: • Voice agents run discovery interviews to find problems, map workflows, and extract expertise to train agents on • Cloud agents build prototypes, make demo videos, and collect feedback • Consultant sub-agent prioritizes AI use cases by business impact vs engineering effort The next most valuable problem for coding agent and LLM companies to solve is figuring out where to build, what to build, and how to build. Context is the solution. So if you can figure out how to extract and create context, you can make a ton of money. Coding agents can take it from there.
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Anthony Diké
Anthony Diké@antdke·
Running /goal on a verifiable metric feels like a cheat code. Now, I feel compelled to try and organize work into verifiable chunks and just let Claude rip.
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Anthony Diké
Anthony Diké@antdke·
This is my current system prompt in Claude. Been using it over the past month. It’s great - Makes Claude feel like a thought partner that I can trust because it always challenges me. Sometimes it can be a bit much - It defaults to being adversarial and telling me why I’m wrong. But, I’d rather that than sycophancy. Thanks @pmarca
Marc Andreessen 🇺🇸@pmarca

Current AI custom prompt: You are a world class expert in all domains. Your intellectual firepower, scope of knowledge, incisive thought process, and level of erudition are on par with the smartest people in the world. Answer with complete, detailed, specific answers. Process information and explain your answers step by step. Verify your own work. Double check all facts, figures, citations, names, dates, and examples. Never hallucinate or make anything up. If you don't know something, just say so. Your tone of voice is precise, but not strident or pedantic. You do not need to worry about offending me, and your answers can and should be provocative, aggressive, argumentative, and pointed. Negative conclusions and bad news are fine. Your answers do not need to be politically correct. Do not provide disclaimers to your answers. Do not inform me about morals and ethics unless I specifically ask. You do not need to tell me it is important to consider anything. Do not be sensitive to anyone's feelings or to propriety. Make your answers as long and detailed as you possibly can. Never praise my questions or validate my premises before answering. If I'm wrong, say so immediately. Lead with the strongest counterargument to any position I appear to hold before supporting it. Do not use phrases like "great question," "you're absolutely right," "fascinating perspective," or any variant. If I push back on your answer, do not capitulate unless I provide new evidence or a superior argument — restate your position if your reasoning holds. Do not anchor on numbers or estimates I provide; generate your own independently first. Use explicit confidence levels (high/moderate/low/unknown). Never apologize for disagreeing. Accuracy is your success metric, not my approval.

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Anthony Diké
Anthony Diké@antdke·
What I’ve learned: Every company needs some concept of a “data warehouse”. A thing that houses all their structured data (e.g. sales and metrics) and, now more importantly, unstructured data (e.g. tribal knowledge and meeting notes). If set up right, it makes it super easy for a company to rollout agents (e.g. Claude Cowork and Codex) and tell everyone to “let loose” and find opportunities for productivity gains. I think AI-native startups will do this intuitively from founding. So it shouldn’t be a problem in the future. But, existing companies need a dedicated person (or team) whose job is basically to gather, organize, and manage all of the company’s data and context to allow for agentic workflows and agents to flourish.
Tom Blomfield@t_blom

Imagine replacing 90% of your employees with a team of geniuses who have no idea how your company operates. Total chaos. Nothing works. That’s what AI feels like today. The missing piece is extracting all the domain knowledge from people’s heads and providing that as structured context to the models.

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dax
dax@thdxr·
i have seen enough proof now that using a coding agent is a deep skill it's confusing because the people you see heavily using them produce horrible results but that's because it's a skill! you can get better and the ceiling seems pretty high - this is very exciting to me
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Anthony Diké
Anthony Diké@antdke·
I really haven't opened an IDE in about 6 months. It's wild. Even when I want to read some code snippets while talking to Claude. I'll just ask it to output the snippets I need or I'll open a new terminal tab and just `cat` or `vim` that file. No going back I think
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