... finally read the whole study instead of the headline, and the actually useful findings are different from what got shared. First, in their realistic-config lane (instruction file + several MCP servers), the "light" harness came out HEAVIER: ~90.8k vs ~75k. A 72KB instruction file alone added ~20k tokens to every request, on both harnesses. Their own conclusion: configuration, not the harness, accounts for most of the production bill. The harness sets the floor, you set the ceiling. Second ... ... this is the one that changed how I think about it: the cache behavior gap was way bigger than the size gap. The light harness kept its prefix

... agent didn't just act, it acted with someone's credentials, someone's access, someone's blast radius. and when it goes wrong, the audit trail usually can't tell you what the agent was actually authorised to do versus what it happened to have access to. those are different things and most systems conflate them. honestly that's a big part of why we're building MonoCloud the way we are. scoped identity for agents so the blast radius ... ... because it's dumb, but because the radius is determined by capabilities it isn't even looking at. That's the strongest version of the "worst judge of its own reach" point I've seen. And your authority-armed-versus

... still fetch on its own is a different kind of leak than the one being sandboxed against. Comment from Gal Dayan(@galdayan): @swapnanil_ray  worth flagging: prompt caching helps the cost of re-reading the same conversation prefix, but it doesn't change that you're still regenerating a whole new artifact for what's structurally a filter, not a new question. those are two separate problems wearing one label. might be worth a cheaper "patch" path ...

... worker. For UI testing, a remote headed browser is not just a convenience. It changes the debugging loop. Instead of asking "what did the script think happened?", you can ask "what did the user actually see?" ### Harness Code vs Local Agent Harness Another important decision is where the agent capability should come from. One option is to build the entire reasoning layer yourself: call an LLM API directly, manage prompts, retries, tool calls, screenshots, JSON parsing, and safety rules. That ... ... gives maximum control, but it also means the test harness becomes an AI platform project. The alternative

... revenue, but the same shape hit our deliverability instead of our billing: an AI-run outreach batch bounced 17 of 36 sends (47%) to real business inboxes, then the AI-authored "fix" just guessed a different address prefix at the same domains and bounced the same outlets again six hours later. Same root cause as yours: a silent failure mode nobody had put a hard-stop invariant around. "Zero is a valid float" has a sibling in our world ...

... Breakdown Anthropic Claude Sonnet pricing: Input: $3 per million tokens Output: $15 per million tokens (unchanged by compression) Cached input: $0.30 per million tokens (90% discount) My savings come from two sources: Fewer input tokens (compression) More cache hits (prefix stabilization) Metric Before After Daily input tokens 990K 268K Cache hit rate 12% 48% Effective input cost/day $2.90 $0.62 Output cost/day (unchanged) $7.50 $7.50 Daily total $10.40 $8.12 Wait, that is only $68/month savings on raw math. Where does ... ... file reads, fewer redundant tool calls, fewer wasted output tokens on re-doing work. Does Quality Actually Stay the Same? I was skeptical too. Here is what I measured over 4 weeks: Code that compiles first try: 78% (before) vs

... dependency graph. For those shipping SDKs: do you find that keeping the SDK code in the same monorepo helps the AI write better integration tests, or does it get confused by the different environments (e.g., std for SDK vs no_std for core)? Comment from Raj Kumar(@new_user___0932026a86e905cf4b2b7f7): Submodules felt powerful in theory but in practice they kept getting in the way. The constant syncing and broken context made development slower than expected. Switching to a cleaner monorepo ... ... command look like? Curious how you scripted it. Comment from Csaba Ivancza(@csaba_ivancza): @second_son_of_god  i have a bash script that handles all the subtree management, but the important part is here: git subtree push --prefix

... only needs to specify what's changing the executor fills in the rest. 2. LLMs hallucinate success when API calls fail A tool returns a 404. The agent says "done, the record was updated!" The fix: explicitly prefix every error response with "Error:" and add one line to the system prompt if a tool returns a message starting with Error:, report it directly. Do not assume success. Without this, the agent will confidently lie every time. 3. Query parameters break ... ... Comment from Shyun Bill(@shyunbill): The "silent wipe" on partial updates is a total nightmare that still catches the best of us! It s wild how these models will lie about success just to stay "helpful," so that "Error:" prefix

... same time also feature rich database we could find. Thank you DuckDB team! It creates a new OpenClaw profile called dench , and opens a new OpenClaw Gateway that means you can run all your usual openclaw commands by just prefixing every command with `openclaw --profile dench` . It will start your gateway on port 19001 range. You will be able to access the DenchClaw frontend at localhost:3100. Once you open it on Safari, just add it to your Dock ...

... user_carol'], }); // Only alice, bob, and carol can see or update this record // Pass x-subject-id header to identify the caller 6. Cross-References with ref: Types Schema fields can reference other record types using the ref: prefix. This creates typed foreign-key relationships between records that the system can follow automatically. // Define a deals schema that references accounts await mnx.records.defineSchema('deals', { title: { type: 'string', required: true }, value: { type: 'number' }, stage: { type: 'string' }, account_id: { type: 'ref:accounts', description ...

... Features Here s what FastTempMail offers: Multiple Sessions Use up to 3 emails at once Custom Duration Choose how long your inbox lives ( 1 hour to 3 days ) Real-Time Auto-refresh inbox with no manual reload Custom Prefix Create personalized email prefixes

... websites , PDFs, images, and files Scrape web pages into markdown optimized for an LLM Crawl search engines for up-to-date knowledge Extract JSON from web pages using natural language It's almost too easy to get started: simply prefix a given URL with ` https://pure.md/ `. I use it myself to easily pipe webpage content directly into an LLM, knowing that all the superfluous HTML will be stripped out so that the input token count remains ...

... start, I can't believe I didn't know this - A friend taught me earlier today regarding the "plus trick", also known as "plus addressing", for Gmail addresses. You simply type in + after the prefix of your email address along with any text, and any email sent to this will still arrive in your inbox. For example: If my email is sean@gmail.com , any emails sent to sean +business @gmail.com, sean +product @gmail.com, will still arrive in the inbox of sean@gmail.com ...