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Hashnode
Internet Publishing
San Francisco, California 28,250 followers
The blogging platform where builders in tech write, get found, and own their audience.
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Hashnode is the blogging platform for builders in tech.
A brand-new blog starts with zero search authority. An article on Hashnode does not. Articles published here rank in search and get cited by AI engines from day one, so your writing reaches readers instead of sitting on an island. You build on the network's reach while keeping your own domain and your own audience.
Write in a fast, distraction-free editor built for technical content: code blocks with syntax highlighting, LaTeX math, tables, and rich embeds. Publish to a hashnode.dev subdomain or map your own custom domain. Own your work, with no lock-in.
For teams, run a publication together with roles, contributor review, and shared analytics, without standing up a CMS.
Hashnode Pro unlocks the power-user layer for any publication:
• Custom domain
• GraphQL API and headless mode (use Hashnode as a headless CMS)
• AI writing tools in the editor
• Webhooks and GitHub backup
• Bulk Markdown import
• Remove Hashnode branding
Pricing is simple and per publication: $5 per seat each month, or $50 a year with two months free. Start free, and go Pro only on the publications that need it.
Who it's for: developers, engineers, technical writers, DevRel teams, and the builders around them who want their work found and owned.
Start writing at hashnode.com.
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Shekhar Kirani is an Influencer
Accel in India. Early-stage and growth-stage technology investor.
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Hashnode reposted this
Sandeep Panda
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Introducing Dear Agent: give your agents inboxes instantly. 100% open source, and self-hosted on Cloudflare .
Built using Cloudflare Workers, D1, R2 and Email Routing features.
Try it now at dearagent.sh and send your contributions on GitHub.
https://lnkd.in/gUTdbJr8
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Hashnode reposted this
Fazle Rahman
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linear integration just shipped
connect your workspace, pick the labels to watch, and any issue wearing one gets picked up by the software factory: cloned into an isolated sandbox, built, run against your repo's own lint and tests, QA'd in a real browser with the session recorded, then opened as a pull request back on the ticket
the video is a real run. i didn't prompt it and i didn't open localhost, i just put a label on a ticket
which is the part that still gets me. a software factory is only worth anything if work gets in without you, and a label is about as little ceremony as intake gets. writing a clear ticket was always the real work. now it's the only one
if you want to see it on your own repo we'll pull a real ticket off your backlog and run it live: darkshift.dev
#softwarefactory #qa #ai
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We've introduced a new Growth Plan: everything in Pro, plus an AEO toolkit for a flat $29 a month.
Your next reader asks ChatGPT, gets one answer, and never sees a results page.
The toolkit is built for that:
- AEO score in the editor, eight checks before you publish
- FAQ blocks that ship as structured data
- Per-bot robots.txt toggles for AI crawlers, plus an llms.txt index of your posts
- Freshness queue so you know what to update next
- Daily checks on whether ChatGPT, Claude, Gemini, and Perplexity cite you
Upgrade from your dashboard's billing page.
Full details are on http://hashnode.com/pro
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Hashnode reposted this
Fazle Rahman
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adoption for v0, replit, and lovable has only gone up in the last few months. but as products built with these tools scale… you can't go prompt to production without verifying what actually works.
so we're taking the ADLC further. a software factory builds the next feature and leaves a pr ready to ship with a verifiable QA video attached. if the QA fails, it loops and keeps working until it passes.
Spotify, Uber and Ramp already spend quarters building factories like this internally. high-growth startups can't afford that.
we built darkshift for ourselves and have shipped a lot of features with it at Hashnode and Bug0 over the last 8 weeks. now it has a name and a website.
it's invite-only for now, normally $99/user/month. i'll waive the platform fee for 12 months in exchange for feedback. darkshift.dev
Sandeep Panda
Replacing brittle test scripts with agentic AI. Building Bug0, AI-native prompt-to-test e2e testing platform.
4w
Introducing Darkshift, a software factory we’ve been using at Hashnode and Bug0.
Today, for the first time, we're opening it up to others and we'd love some feedback!
The idea is simple: software development should be able to run entirely in the cloud, in the background, without you babysitting coding agents or setting up local environments.
Personally, I haven't touched my local dev setup at all after using Darkshift.
With Darkshift, you can:
> Choose between Claude Code, Codex, Grok Build or Kimi Code
> BYOK or bring your Codex subscription
> Work entirely from the cloud - no local dev needed
> Start work from the web, Slack or Linear
> Get evidence-backed PRs when the work is done
> Collaborate with your team
> Get a self-improving system that gets better every time you use it
Since the last November, models have become much more capable. We're reaching a point where it's neither practical nor necessary to read every line of code they produce.
With a dark factory, the process can be dark but the output shouldn't be. The output is a PR you can read, inspect, run, and verify. With enough testing, agentic inquiry, and evidence around every change, you can trust the outcome without having to watch every step that produced it.
Darkshift is built around these principles.
We’re keeping access waitlisted for now.
Darkshift is $99/user/month, but for the first batch of users, I’ll waive the platform fee for 12 months in exchange for feedback.
If you want to try it, DM me.
Excited (and slightly nervous) to finally let people outside our teams use this.
Sign up at https://darkshift.dev
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Hashnode reposted this
Sandeep Panda
4w
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Introducing Darkshift, a software factory we’ve been using at Hashnode and Bug0.
Today, for the first time, we're opening it up to others and we'd love some feedback!
The idea is simple: software development should be able to run entirely in the cloud, in the background, without you babysitting coding agents or setting up local environments.
Personally, I haven't touched my local dev setup at all after using Darkshift.
With Darkshift, you can:
> Choose between Claude Code, Codex, Grok Build or Kimi Code
> BYOK or bring your Codex subscription
> Work entirely from the cloud - no local dev needed
> Start work from the web, Slack or Linear
> Get evidence-backed PRs when the work is done
> Collaborate with your team
> Get a self-improving system that gets better every time you use it
Since the last November, models have become much more capable. We're reaching a point where it's neither practical nor necessary to read every line of code they produce.
With a dark factory, the process can be dark but the output shouldn't be. The output is a PR you can read, inspect, run, and verify. With enough testing, agentic inquiry, and evidence around every change, you can trust the outcome without having to watch every step that produced it.
Darkshift is built around these principles.
We’re keeping access waitlisted for now.
Darkshift is $99/user/month, but for the first batch of users, I’ll waive the platform fee for 12 months in exchange for feedback.
If you want to try it, DM me.
Excited (and slightly nervous) to finally let people outside our teams use this.
Sign up at https://darkshift.dev
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Hashnode
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A clean explainer on what a background coding agent actually is, and how it differs from the tools people already have open.
The framing that makes it click: sort AI coding tools by how often a human closes the loop. Autocomplete asks every few seconds. IDE agents like Cursor and Claude Code ask every few minutes. Background agents run in a cloud sandbox and ask once, at the pull request. Same models underneath. What changes is where the loop runs.
The part I'd underline is what should arrive attached to that pull request. A diff on its own puts the whole verification burden back on the reviewer. The checks it passed, a self-review of the diff, and a recording of the change working in a real browser are what make review quick enough to be worth doing.
There's also a good point on security: safety comes from isolation and scope, not from trusting the model to behave.
https://lnkd.in/eUmv6wFg
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Hashnode
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If you're weighing whether to build an AI software factory in-house, this is the build log to read first. "The coding agent is the part you do not build."
The project is the seven stations around it: isolated execution, snapshot templates, credential handling, git and PR orchestration, a server-owned run loop, live observability, and verification. Verification is the one everyone underestimates, since a green CI run tells you nothing about whether a user-facing change actually works.
Two costs that never reach a budget line. Review attention grows faster than anything on an invoice. And an internal factory is a product with exactly one customer, so somebody owns it for as long as the company runs it, and that name usually gets decided by accident.
The other useful reframe: running cost scales with how many tasks you queue, not how many engineers you employ.
https://lnkd.in/e9eEvET2
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Hashnode
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Sandeep puts the line between agentic coding and vibe coding in the place that actually decides anything, which is where the review happens. "Both start with a prompt. Only one of them ends with somebody reading the diff."
The post comes with three weeks of numbers from a real repo. Agents opened 69 of the 99 PRs that merged, 56 of those went in unchanged, and 13 needed a human to correct them.
The useful finding is what those 13 had in common. Every one was a task where nobody had written down what finished looked like, which makes an 18.8% correction rate a measure of the task description as much as of the agent.
There's also one example that justifies the whole review gate: an agent shipped image upload and left the files publicly readable. Review caught it inside a day.
https://lnkd.in/eNuPqanV
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Hashnode
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AI software factory covers four different purchases, and vendors rarely tell you which one you're being shown.
Buy a platform and you get the plumbing between the stages, then you integrate it into your own stack. Assemble one and you pick the sandbox, the coding agent, the verification layer and the credential broker separately. Self-host the lot if compliance says code cannot leave the network. Or have one built inside your environment and handed over to you.
The stages are the same in every case: intake, isolation, implementation, verification, pull request. What changes is who does the integration work, and how long you wait for the first PR.
Two things I'd check before sitting through a demo. Isolation is harder than it looks and gets underestimated in almost every plan. And assembled stacks tend to drop verification, which leaves you with an agent that opens pull requests nobody trusts. There is also no published first-attempt merge rate from anyone, so you cannot compare reliability across vendors yet.
The tools available at each layer: https://lnkd.in/eVxMBMPY
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Hashnode
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Everyone is suddenly building an AI software factory: a system where coding agents take a ticket to a verified pull request with no human in the middle. The term is from Hitachi in 1969, and this is its third revival.
What strikes me about the category is how converged it already is. Devin, Factory, 8090, and FactoryKit all run the same five stages: intake, isolation, implementation, verification, PR. When four vendors independently arrive at one architecture, that usually means it's durable.
What's missing is measurement. There is no public benchmark for ticket-to-merged-PR reliability across any of these products. The naming is outrunning the measuring, and buying decisions are running on demos.
Full disclosure, we build one of the four, so I wrote this with the gaps in as much detail as the pitch: https://lnkd.in/dnXRW2V7
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