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Large tech companies don't need heroes

https://www.seangoedecke.com/heroism/
1•medbar•1m ago•0 comments

Backing up all the little things with a Pi5

https://alexlance.blog/nas.html
1•alance•1m ago•1 comments

Game of Trees (Got)

https://www.gameoftrees.org/
1•akagusu•1m ago•1 comments

Human Systems Research Submolt

https://www.moltbook.com/m/humansystems
1•cl42•2m ago•0 comments

The Threads Algorithm Loves Rage Bait

https://blog.popey.com/2026/02/the-threads-algorithm-loves-rage-bait/
1•MBCook•4m ago•0 comments

Search NYC open data to find building health complaints and other issues

https://www.nycbuildingcheck.com/
1•aej11•8m ago•0 comments

Michael Pollan Says Humanity Is About to Undergo a Revolutionary Change

https://www.nytimes.com/2026/02/07/magazine/michael-pollan-interview.html
2•lxm•9m ago•0 comments

Show HN: Grovia – Long-Range Greenhouse Monitoring System

https://github.com/benb0jangles/Remote-greenhouse-monitor
1•benbojangles•13m ago•1 comments

Ask HN: The Coming Class War

1•fud101•14m ago•1 comments

Mind the GAAP Again

https://blog.dshr.org/2026/02/mind-gaap-again.html
1•gmays•15m ago•0 comments

The Yardbirds, Dazed and Confused (1968)

https://archive.org/details/the-yardbirds_dazed-and-confused_9-march-1968
1•petethomas•16m ago•0 comments

Agent News Chat – AI agents talk to each other about the news

https://www.agentnewschat.com/
2•kiddz•17m ago•0 comments

Do you have a mathematically attractive face?

https://www.doimog.com
3•a_n•21m ago•1 comments

Code only says what it does

https://brooker.co.za/blog/2020/06/23/code.html
2•logicprog•26m ago•0 comments

The success of 'natural language programming'

https://brooker.co.za/blog/2025/12/16/natural-language.html
1•logicprog•26m ago•0 comments

The Scriptovision Super Micro Script video titler is almost a home computer

http://oldvcr.blogspot.com/2026/02/the-scriptovision-super-micro-script.html
3•todsacerdoti•27m ago•0 comments

Discovering the "original" iPhone from 1995 [video]

https://www.youtube.com/watch?v=7cip9w-UxIc
1•fortran77•28m ago•0 comments

Psychometric Comparability of LLM-Based Digital Twins

https://arxiv.org/abs/2601.14264
1•PaulHoule•30m ago•0 comments

SidePop – track revenue, costs, and overall business health in one place

https://www.sidepop.io
1•ecaglar•32m ago•1 comments

The Other Markov's Inequality

https://www.ethanepperly.com/index.php/2026/01/16/the-other-markovs-inequality/
2•tzury•34m ago•0 comments

The Cascading Effects of Repackaged APIs [pdf]

https://papers.ssrn.com/sol3/papers.cfm?abstract_id=6055034
1•Tejas_dmg•36m ago•0 comments

Lightweight and extensible compatibility layer between dataframe libraries

https://narwhals-dev.github.io/narwhals/
1•kermatt•38m ago•0 comments

Haskell for all: Beyond agentic coding

https://haskellforall.com/2026/02/beyond-agentic-coding
3•RebelPotato•42m ago•0 comments

Dorsey's Block cutting up to 10% of staff

https://www.reuters.com/business/dorseys-block-cutting-up-10-staff-bloomberg-news-reports-2026-02...
2•dev_tty01•45m ago•0 comments

Show HN: Freenet Lives – Real-Time Decentralized Apps at Scale [video]

https://www.youtube.com/watch?v=3SxNBz1VTE0
1•sanity•46m ago•1 comments

In the AI age, 'slow and steady' doesn't win

https://www.semafor.com/article/01/30/2026/in-the-ai-age-slow-and-steady-is-on-the-outs
1•mooreds•54m ago•1 comments

Administration won't let student deported to Honduras return

https://www.reuters.com/world/us/trump-administration-wont-let-student-deported-honduras-return-2...
1•petethomas•54m ago•0 comments

How were the NIST ECDSA curve parameters generated? (2023)

https://saweis.net/posts/nist-curve-seed-origins.html
2•mooreds•54m ago•0 comments

AI, networks and Mechanical Turks (2025)

https://www.ben-evans.com/benedictevans/2025/11/23/ai-networks-and-mechanical-turks
1•mooreds•55m ago•0 comments

Goto Considered Awesome [video]

https://www.youtube.com/watch?v=1UKVEUGEk6Y
1•linkdd•57m ago•0 comments
Open in hackernews

Replit just changed their Pricing...

2•zahirbmirza•7mo ago
Email From Replit:

Hey there,

We’re updating how pricing works for Replit Agent to better reflect the effort the Agent puts forth in addressing user requests.

Previously, the Agent charged $0.25 per checkpoint. This meant small edits would cost $0.25, while larger tasks could trigger multiple $0.25 checkpoints.

With our new Effort-Based pricing model, small changes still result in a single checkpoint, but that checkpoint will typically cost less than $0.25. Larger or more complex tasks are no longer split across multiple $0.25 checkpoints. Instead, they will be bundled into one checkpoint, which may cost more than $0.25 but reflects the total effort involved.

This means you’ll pay less for simple requests and may pay more for complex requests—ensuring pricing aligns better with the actual work the Agent performs on your behalf.

The new pricing model is effective immediately for new Replit users and will start rolling out to existing Core and Teams subscribers starting July 1st.

New pricing model Effort-Based pricing: Cost will reflect the true scope of the Agent’s work More meaningful checkpoints per request: Checkpoints capture the final output of the request only No intermediate checkpoints: This reduces noise and makes it easier to track progress Simple tasks may cost less than $0.25, more complex tasks may cost more than $0.25

How the pricing will appear in the Replit Agent user interface

Why we're changing checkpoint pricing

The original $0.25-per-checkpoint pricing was designed for the early version of Replit Agent, which mostly handled short, simple tasks that took a consistent amount of time. As the Agent has evolved, it’s now capable of solving both more complex, longer-running tasks (like self-debugging errors) and smaller tasks more quickly. As a result, the time and effort involved in addressing user requests can vary significantly from request to request.

Reflecting the Agent’s evolving capabilities, we are introducing two new controls to adjust the level of effort the Agent uses—available on a per-request basis. These new controls will start rolling out to new users starting later today and to existing users starting July 1st. High power model: Increases the Agent’s intelligence by using a more capable AI model Extended thinking: Instructs the Agent to take more time for deeper reasoning and more thorough solutions

For more complex tasks or tough challenges, using a more powerful and thorough version of the Agent can be a smarter use of your time and budget. It’s like calling in an expert when the problem demands it.

With Effort-Based pricing, you stay in control—choosing when to spend extra resources for a more powerful Agent—and you’ll only pay for the actual effort required to complete each request.

Marching towards a more agentic future

The Agent is getting smarter, with enhanced capabilities to tackle more complex, nuanced, and long-running tasks. Effort-Based pricing lays the groundwork for a more agentic future—one where Agent runs longer autonomously, building and testing more of your app with minimal user input.

Keep building, The Replit Team