Ashkrit Sharma

LIFE IS LIKE RIDING A BICYCLE. TO KEEP YOUR BALANCE YOU MUST KEEP MOVING” A. EINSTEIN

[Ashkrit Sharma @ashkrit]

How AI companies spent billions rediscovering something TCS / Infosys / Accenture / Thought works  figured out decades back — and why the pattern was always going to repeat.

#ForwardDeployedEnginner

https://t.co/nc0z3xzUQs

[Ashkrit Sharma @ashkrit]

From git clone to llm clone

llm clone https://t.co/obzJpZVura

https://t.co/56iPBMnAlH

[Ashkrit Sharma @ashkrit]

Building on Rented Ground
On April 22, 2026, Anthropic changed a checkbox on a pricing page. No announcement. No email. No deprecation notice. Just a quiet edit — and overnight, Claude Code disappeared from the $20/month Pro plan.
https://t.co/VDiH2TzKNT

[Ashkrit Sharma @ashkrit]

Stop Reaching out to Agents
Industry keeps pushing toward the flashiest pattern on the menu, and teams keep mistaking complexity for capability. The truth is boringly simple: you should have to be forced up the ladder, not invited.
#AgenticPatterns
https://t.co/6SOJHLpFO2

[Ashkrit Sharma @ashkrit]

Jeff Bezos had a simple heuristic for team size: if two pizzas can't feed the team, the team is too big. It was never really about pizza.

https://t.co/pHewMXbFNi

#AgenticAgile

[Ashkrit Sharma @ashkrit]

Great Claude Code Leak and Under the hood - Claude code | Codex | Gemini

Every system prompt is a Natural Language Program,  list of instructions — a code of how an AI agent becomes reliable.

https://t.co/AKH13Rqynh

#ClaudeCode #PromptDesign

[Ashkrit Sharma @ashkrit]

AI Engineering Terms You Will Memorize and then forget

LLM era has a reliable product cycle: someone coins a term, someone more famous endorses it, the internet credits the endorser, and LinkedIn does the rest.

https://t.co/og4pnXL3Y0

[Ashkrit Sharma @ashkrit]

Similarity is not Relevance
LLMs are similarity machines. Every layer — retrieval, generation, alignment — optimizes for proximity.
But similarity is geometric. Relevance is teleological.
One asks: how close? The other asks: does this help?

https://t.co/qKmMhuTjM0

[Ashkrit Sharma @ashkrit]

https://t.co/6bQ4vht5xM

[Ashkrit Sharma @ashkrit]

Revisiting Classic paper - tail at scale

https://t.co/9B2FTX0KMm

[Ashkrit Sharma @ashkrit]

Why the AI your company just mandated was designed for a boardroom slide, not your workflow — and how the whole machine keeps spinning.

https://t.co/6iVJQnDzGu

[Ashkrit Sharma @ashkrit]

@calcsam BOOK. I love it

[Ashkrit Sharma @ashkrit]

@cline
Post on Cline - Overview - How it does magic
https://t.co/CwkfLglmIT

[Ashkrit Sharma @ashkrit]

@henrythe9ths AI guide looks interesting

[Ashkrit Sharma @ashkrit]

New Blog Post on -
Say Goodbye to Boilerplate: Annotating Your Way to Powerful API Clients
https://t.co/mUxI1O1P0A

[Ashkrit Sharma @ashkrit]

Blog post on Vector database

https://t.co/UEVBLP1PQo

[Ashkrit Sharma @ashkrit]

Blog post of Data structure that supports access pattern of Map + Sorted by X attributes.

https://t.co/QRZaZamRxf

[Denis Magda @denismagda]

Amazing! A 17-year-old teenager created this while striving to understand how applications are executed: https://t.co/KmwsywV0oI

The book explains:
* How CPUs execute your app's instructions
* How the OS uses interrupts to switch CPUs between tasks
* The way virtual memory allocates physical memory among processes
* The processes of app compilation and linkage

[Vivek Sen @Vivek4real_]

@saifedean @aantonop @skwp @egg_descrambler 7)
"Layered Money" by @timevalueofbtc

Bhatia offers an innovative perspective on #Bitcoin 's potential to become the first layer in the future of finance. It's a thought-provoking exploration of Bitcoin's role in the financial ecosystem.

[Daniel Mahncke @MnkeDaniel]

Biases that distort our Decision Making:

1. Confirmation Bias - We interpret new information as confirmation of our existing beliefs.

2. Availability Bias - We tend to rely on information that comes to our mind easily/the quickest.

3. Action Bias - We favor action over inaction.
That's why we sell or buy prematurely.

4. Overconfidence - We overestimate our own knowledge and ability.

Often because we know too little to know better.
(Less knowledge => more confidence)

5. Survivorship Bias - This is a sample bias that occurs when we assess only successful outcomes and disregard failures.

What Biases do you struggle the most with?