After 6 years of R&D, our small team is excited to share our project TideCloak - an IAM designed to help developers move fast without worrying about catastrophic breaches or overpowered admins with keys to the kingdom.
Traditional IAMs rely on centralized authority - admins, root certificates, and decryption keys - which create glaring vulnerabilities in a breach. To address this, we\u2019ve integrated Keycloak (Red Hat\u2019s IAM) with a decentralized key architecture powered by our (academically validated) Ineffable Cryptography.
Here\u2019s the idea: keys are split across a decentralized network (our Cybersecurity Fabric) so no one ever holds the full key. Even in a breach or F$%k up, there\u2019s no unchecked authority exposed.
Right now, TideCloak uses the Cybersecurity Fabric as an IdP, meaning users authenticate without their credentials being stored or shared. Essentially, users bring their own authority - without needing to trust anyone else to keep it safe.
Coming soon:\n- Identity Governance Administration to prevent super admin abuse.\n- User-sovereign digital assets, where assets are secured with unique decentralized keys to protect against mass breaches.
We\u2019ve just launched a free developer sandbox, and we\u2019d love your feedback:\nhttps://github.com/tide-foundation/tidecloak-gettingstarted
It\u2019s still early stages, and your input will help us improve.
Thanks for taking a look - ask us anything!"},"title":{"matchLevel":"none","matchedWords":[],"value":"Show HN: TideCloak \u2013 Decentralized IAM for security and user sovereignty"},"url":{"matchLevel":"none","matchedWords":[],"value":"https://github.com/tide-foundation/tidecloak-gettingstarted"}},"_tags":["story","author_SaltNHash","story_42460131","show_hn"],"author":"SaltNHash","children":[42464970,42465138,42465497,42465734,42466080,42466415,42467475,42467560,42490604,42490823,42490937,42494364],"created_at":"2024-12-19T10:17:52Z","created_at_i":1734603472,"num_comments":36,"objectID":"42460131","points":54,"story_id":42460131,"story_text":"Hey HN!
After 6 years of R&D, our small team is excited to share our project TideCloak - an IAM designed to help developers move fast without worrying about catastrophic breaches or overpowered admins with keys to the kingdom.
Traditional IAMs rely on centralized authority - admins, root certificates, and decryption keys - which create glaring vulnerabilities in a breach. To address this, we\u2019ve integrated Keycloak (Red Hat\u2019s IAM) with a decentralized key architecture powered by our (academically validated) Ineffable Cryptography.
Here\u2019s the idea: keys are split across a decentralized network (our Cybersecurity Fabric) so no one ever holds the full key. Even in a breach or F$%k up, there\u2019s no unchecked authority exposed.
Right now, TideCloak uses the Cybersecurity Fabric as an IdP, meaning users authenticate without their credentials being stored or shared. Essentially, users bring their own authority - without needing to trust anyone else to keep it safe.
Coming soon:\n- Identity Governance Administration to prevent super admin abuse.\n- User-sovereign digital assets, where assets are secured with unique decentralized keys to protect against mass breaches.
We\u2019ve just launched a free developer sandbox, and we\u2019d love your feedback:\nhttps://github.com/tide-foundation/tidecloak-gettingstarted
It\u2019s still early stages, and your input will help us improve.
Thanks for taking a look - ask us anything!","title":"Show HN: TideCloak \u2013 Decentralized IAM for security and user sovereignty","updated_at":"2025-07-13T19:25:50Z","url":"https://github.com/tide-foundation/tidecloak-gettingstarted"},{"_highlightResult":{"author":{"matchLevel":"none","matchedWords":[],"value":"mooseburger"},"story_text":{"fullyHighlighted":false,"matchLevel":"full","matchedWords":["ineffable"],"value":"I have some idle time and have been asked to look into producing a code review checklist. This is quite an interesting matter, as to me, much like programming, code reviewing is a highly idiosyncratic, ineffable, thing, and so I wonder whether the community here has somehow managed to formalize it.
There are obvious things to put in such a checklist (e.g. short and legible methods, check for potential null reference exceptions) but sometimes even glaring bugs can sneak through code review. A recent example: in a PR, I noticed a method call had been deleted and replaced with nothing, and asked the developer about it. The developer assured me the functionality that the method had provided was implemented elsewhere in the PR, and that indeed seemed to be the case.
Turns out, that other implementation did not in fact cover all the functionality the deleted method call had provided, and an entire feature was lost due to that PR. In light of this, something else that could go in a checklist is "when a method call is deleted, verify what the method did". Another is that deleting that method call meant the method had no references (dead code), yet was not deleted, so neither I nor the other reviewers saw the method body in the diff, which would have shown that a feature was being lost. Another item could be "If method calls are deleted, check for dead code".
Do you have a formal method for conducting code reviews? What things do you look for?"},"title":{"matchLevel":"none","matchedWords":[],"value":"Ask HN: How do you conduct code reviews?"}},"_tags":["story","author_mooseburger","story_19107821","ask_hn"],"author":"mooseburger","children":[19108992,19109649,19112782,19113233,19114284,19120165,19121899],"created_at":"2019-02-07T19:37:42Z","created_at_i":1549568262,"num_comments":7,"objectID":"19107821","points":12,"story_id":19107821,"story_text":"I have some idle time and have been asked to look into producing a code review checklist. This is quite an interesting matter, as to me, much like programming, code reviewing is a highly idiosyncratic, ineffable, thing, and so I wonder whether the community here has somehow managed to formalize it.
There are obvious things to put in such a checklist (e.g. short and legible methods, check for potential null reference exceptions) but sometimes even glaring bugs can sneak through code review. A recent example: in a PR, I noticed a method call had been deleted and replaced with nothing, and asked the developer about it. The developer assured me the functionality that the method had provided was implemented elsewhere in the PR, and that indeed seemed to be the case.
Turns out, that other implementation did not in fact cover all the functionality the deleted method call had provided, and an entire feature was lost due to that PR. In light of this, something else that could go in a checklist is "when a method call is deleted, verify what the method did". Another is that deleting that method call meant the method had no references (dead code), yet was not deleted, so neither I nor the other reviewers saw the method body in the diff, which would have shown that a feature was being lost. Another item could be "If method calls are deleted, check for dead code".
Do you have a formal method for conducting code reviews? What things do you look for?","title":"Ask HN: How do you conduct code reviews?","updated_at":"2024-09-20T03:39:11Z"},{"_highlightResult":{"author":{"matchLevel":"none","matchedWords":[],"value":"bbertucc"},"story_text":{"fullyHighlighted":false,"matchLevel":"full","matchedWords":["ineffable"],"value":"A friend said "no salary" startups succeed less than startups where founders take salary. I can't find any info to confirm / deny this.
My case: My company has no revenue yet. I have enough savings to live comfortably for several years. Raising money takes time from developing the product and also means I give away equity. A salary would probably focus my attention more on the company, but "focus" seems ineffable.
What else should I consider about taking a salary during a pre-revenue stage?"},"title":{"matchLevel":"none","matchedWords":[],"value":"Ask HN: Should I take a salary for my pre-revenue startup?"}},"_tags":["story","author_bbertucc","story_27425854","ask_hn"],"author":"bbertucc","children":[27425873,27434976,27435500,27442075],"created_at":"2021-06-07T18:03:24Z","created_at_i":1623089004,"num_comments":6,"objectID":"27425854","points":3,"story_id":27425854,"story_text":"A friend said "no salary" startups succeed less than startups where founders take salary. I can't find any info to confirm / deny this.
My case: My company has no revenue yet. I have enough savings to live comfortably for several years. Raising money takes time from developing the product and also means I give away equity. A salary would probably focus my attention more on the company, but "focus" seems ineffable.
What else should I consider about taking a salary during a pre-revenue stage?","title":"Ask HN: Should I take a salary for my pre-revenue startup?","updated_at":"2024-09-20T08:42:20Z"},{"_highlightResult":{"author":{"matchLevel":"none","matchedWords":[],"value":"SQL2219"},"title":{"matchLevel":"none","matchedWords":[],"value":"Chemist Uses CO2 to Convert Seawater into Drinking Water"},"url":{"fullyHighlighted":false,"matchLevel":"full","matchedWords":["ineffable"],"value":"https://www.ineffableisland.com/2020/10/chemist-uses-co2-to-convert-seawater.html"}},"_tags":["story","author_SQL2219","story_24714760"],"author":"SQL2219","children":[24714781,24715663,24715679,24715846,24716576,24717893,24717988,24718205,24719599,24719607,24719885,24719907,24724262],"created_at":"2020-10-08T01:34:41Z","created_at_i":1602120881,"num_comments":49,"objectID":"24714760","points":217,"story_id":24714760,"title":"Chemist Uses CO2 to Convert Seawater into Drinking Water","updated_at":"2025-07-31T15:01:16Z","url":"https://www.ineffableisland.com/2020/10/chemist-uses-co2-to-convert-seawater.html"},{"_highlightResult":{"author":{"matchLevel":"none","matchedWords":[],"value":"brandonb"},"title":{"matchLevel":"none","matchedWords":[],"value":"A Man Behind AlphaGo Thinks AI Is Taking the Wrong Path"},"url":{"fullyHighlighted":false,"matchLevel":"full","matchedWords":["ineffable"],"value":"https://www.wired.com/story/david-silver-ai-ineffable-intelligence-reinforcement-learning/"}},"_tags":["story","author_brandonb","story_47922664"],"author":"brandonb","children":[47925841,47927071],"created_at":"2026-04-27T15:09:21Z","created_at_i":1777302561,"num_comments":2,"objectID":"47922664","points":7,"story_id":47922664,"title":"A Man Behind AlphaGo Thinks AI Is Taking the Wrong Path","updated_at":"2026-04-28T21:15:31Z","url":"https://www.wired.com/story/david-silver-ai-ineffable-intelligence-reinforcement-learning/"},{"_highlightResult":{"author":{"matchLevel":"none","matchedWords":[],"value":"mikhael"},"title":{"matchLevel":"none","matchedWords":[],"value":"The Man Behind AlphaGo Thinks AI Is Taking the Wrong Path"},"url":{"fullyHighlighted":false,"matchLevel":"full","matchedWords":["ineffable"],"value":"https://www.wired.com/story/david-silver-ai-ineffable-intelligence-reinforcement-learning/"}},"_tags":["story","author_mikhael","story_47955218"],"author":"mikhael","created_at":"2026-04-29T21:50:20Z","created_at_i":1777499420,"num_comments":0,"objectID":"47955218","points":5,"story_id":47955218,"title":"The Man Behind AlphaGo Thinks AI Is Taking the Wrong Path","updated_at":"2026-04-30T06:37:51Z","url":"https://www.wired.com/story/david-silver-ai-ineffable-intelligence-reinforcement-learning/"},{"_highlightResult":{"author":{"matchLevel":"none","matchedWords":[],"value":"fmihaila"},"title":{"matchLevel":"none","matchedWords":[],"value":"The Man Behind AlphaGo Thinks AI Is Taking the Wrong Path"},"url":{"fullyHighlighted":false,"matchLevel":"full","matchedWords":["ineffable"],"value":"https://www.wired.com/story/david-silver-ai-ineffable-intelligence-reinforcement-learning/"}},"_tags":["story","author_fmihaila","story_47929069"],"author":"fmihaila","created_at":"2026-04-28T00:35:43Z","created_at_i":1777336543,"num_comments":0,"objectID":"47929069","points":3,"story_id":47929069,"title":"The Man Behind AlphaGo Thinks AI Is Taking the Wrong Path","updated_at":"2026-04-28T07:09:58Z","url":"https://www.wired.com/story/david-silver-ai-ineffable-intelligence-reinforcement-learning/"},{"_highlightResult":{"author":{"matchLevel":"none","matchedWords":[],"value":"ojarow"},"title":{"matchLevel":"none","matchedWords":[],"value":"Language doesn't perfectly describe consciousness. Can math do better?"},"url":{"fullyHighlighted":false,"matchLevel":"full","matchedWords":["ineffable"],"value":"https://www.vox.com/future-perfect/24125481/consciousness-mental-health-language-science-ineffable-math"}},"_tags":["story","author_ojarow","story_39990899"],"author":"ojarow","created_at":"2024-04-10T14:06:34Z","created_at_i":1712757994,"num_comments":0,"objectID":"39990899","points":2,"story_id":39990899,"title":"Language doesn't perfectly describe consciousness. Can math do better?","updated_at":"2024-09-20T16:55:44Z","url":"https://www.vox.com/future-perfect/24125481/consciousness-mental-health-language-science-ineffable-math"},{"_highlightResult":{"author":{"fullyHighlighted":false,"matchLevel":"full","matchedWords":["ineffable"],"value":"IneffablePigeon"},"story_text":{"matchLevel":"none","matchedWords":[],"value":""},"title":{"matchLevel":"none","matchedWords":[],"value":"Show HN: Orbits.js \u2013 WebGL simulation of the solar system using Three.js"},"url":{"matchLevel":"none","matchedWords":[],"value":"https://github.com/olane/orbits.js"}},"_tags":["story","author_IneffablePigeon","story_8139848","show_hn"],"author":"IneffablePigeon","children":[8143705],"created_at":"2014-08-05T22:19:35Z","created_at_i":1407277175,"num_comments":3,"objectID":"8139848","points":8,"story_id":8139848,"story_text":"","title":"Show HN: Orbits.js \u2013 WebGL simulation of the solar system using Three.js","updated_at":"2023-09-06T22:07:43Z","url":"https://github.com/olane/orbits.js"},{"_highlightResult":{"author":{"matchLevel":"none","matchedWords":[],"value":"vagabund"},"story_text":{"fullyHighlighted":false,"matchLevel":"full","matchedWords":["ineffable"],"value":"It seems to have slipped somewhat under the radar that Anthropic's ChatGPT-competitor Claude is freely available on Quora's Poe [0].
I've spent the last 3 hours with the model learning about Chinese history and culture, including getting recommendations for literature, films, documentaries, and first hand accounts of specific periods. Academic texts from the 1910s and niche foreign language films with only a handful of English reviews were offered without a single hallucination. Historical analyses were nuanced and contextual but highly factual -- I stopped cross-checking info about an hour in, but fabrications were again not an issue.
In addition and in general, and across several conversations on different domains, it exhibits a different caliber of reasoning. It can think strategically about business and markets, it can actually capture something of the essence of an author/poet's voice, and give highly thoughtful critical analysis of texts. It can follow instructions and grok things very quickly.
Beyond that, it has an ineffably human quality that doesn't come through with competitors. Discussions feel vibrant and dynamic, with none of the robotically dull tonality of ChatGPT. And I can't stress enough the difference it makes experientially to not always be second guessing the validity of the output. ChatGPT is great but the spell is broken any time it veers into its own imagined world, here the trust is seldomly misplaced.
I'm sure if you actively went searching for shortcomings or hallucinations you could conjure them, but this thing could be the backbone of a state of the art learning platform today.
[0]: https://poe.com/claude"},"title":{"matchLevel":"none","matchedWords":[],"value":"Tell HN: Anthropic's Claude is significantly better than ChatGPT"}},"_tags":["story","author_vagabund","story_35141867","ask_hn"],"author":"vagabund","children":[35141954,35142278,35142471,35142695,35142919,35143448,35147863,35161240],"created_at":"2023-03-13T20:16:48Z","created_at_i":1678738608,"num_comments":11,"objectID":"35141867","points":19,"story_id":35141867,"story_text":"It seems to have slipped somewhat under the radar that Anthropic's ChatGPT-competitor Claude is freely available on Quora's Poe [0].
I've spent the last 3 hours with the model learning about Chinese history and culture, including getting recommendations for literature, films, documentaries, and first hand accounts of specific periods. Academic texts from the 1910s and niche foreign language films with only a handful of English reviews were offered without a single hallucination. Historical analyses were nuanced and contextual but highly factual -- I stopped cross-checking info about an hour in, but fabrications were again not an issue.
In addition and in general, and across several conversations on different domains, it exhibits a different caliber of reasoning. It can think strategically about business and markets, it can actually capture something of the essence of an author/poet's voice, and give highly thoughtful critical analysis of texts. It can follow instructions and grok things very quickly.
Beyond that, it has an ineffably human quality that doesn't come through with competitors. Discussions feel vibrant and dynamic, with none of the robotically dull tonality of ChatGPT. And I can't stress enough the difference it makes experientially to not always be second guessing the validity of the output. ChatGPT is great but the spell is broken any time it veers into its own imagined world, here the trust is seldomly misplaced.
I'm sure if you actively went searching for shortcomings or hallucinations you could conjure them, but this thing could be the backbone of a state of the art learning platform today.
[0]: https://poe.com/claude","title":"Tell HN: Anthropic's Claude is significantly better than ChatGPT","updated_at":"2024-09-20T13:35:31Z"},{"_highlightResult":{"author":{"matchLevel":"none","matchedWords":[],"value":"caprock"},"title":{"fullyHighlighted":false,"matchLevel":"full","matchedWords":["ineffable"],"value":"Sources of Richness and Ineffability for Phenomenally Conscious States"},"url":{"matchLevel":"none","matchedWords":[],"value":"https://arxiv.org/abs/2302.06403"}},"_tags":["story","author_caprock","story_35204086"],"author":"caprock","created_at":"2023-03-17T23:07:07Z","created_at_i":1679094427,"num_comments":0,"objectID":"35204086","points":1,"story_id":35204086,"title":"Sources of Richness and Ineffability for Phenomenally Conscious States","updated_at":"2024-09-20T13:33:14Z","url":"https://arxiv.org/abs/2302.06403"},{"_highlightResult":{"author":{"matchLevel":"none","matchedWords":[],"value":"hhs"},"title":{"fullyHighlighted":false,"matchLevel":"full","matchedWords":["ineffable"],"value":"Ineffability"},"url":{"fullyHighlighted":false,"matchLevel":"full","matchedWords":["ineffable"],"value":"https://en.wikipedia.org/wiki/Ineffability"}},"_tags":["story","author_hhs","story_22816232"],"author":"hhs","created_at":"2020-04-08T19:37:16Z","created_at_i":1586374636,"num_comments":0,"objectID":"22816232","points":1,"story_id":22816232,"title":"Ineffability","updated_at":"2024-09-20T05:59:00Z","url":"https://en.wikipedia.org/wiki/Ineffability"},{"_highlightResult":{"author":{"matchLevel":"none","matchedWords":[],"value":"jdegoes"},"title":{"fullyHighlighted":false,"matchLevel":"full","matchedWords":["ineffable"],"value":"A fully-inferable, testable effect system for Scala"},"url":{"matchLevel":"none","matchedWords":[],"value":"http://degoes.net/articles/zio-environment"}},"_tags":["story","author_jdegoes","story_19264770"],"author":"jdegoes","created_at":"2019-02-27T17:11:45Z","created_at_i":1551287505,"num_comments":0,"objectID":"19264770","points":1,"story_id":19264770,"title":"A fully-inferable, testable effect system for Scala","updated_at":"2024-09-20T03:53:26Z","url":"http://degoes.net/articles/zio-environment"},{"_highlightResult":{"author":{"matchLevel":"none","matchedWords":[],"value":"johnjcsmith"},"story_text":{"fullyHighlighted":false,"matchLevel":"full","matchedWords":["ineffable"],"value":"Hey HN!
Wanted to share a project I have been working. Data Connector is an open source tool for interacting with Databases (Postgres, MySQL, SQLite) using natural language. Prompts are handled using a ReAct[1] agent which has access to the schema and a tool for executing queries.
It also has experimental[2] support for calling APIs (OpenAPI, GraphQL) which allows for queries that can span multiple systems (Find this user's details in Clerk, etc).
We have mostly been using it for managing our local development environment, but it has configurable controls for running in other environments.
- Privacy Mode which never sends query results back to the LLM context, instead the result is returned to the user as JSON
- Approval Mode which requires manual approval of each query before it is executed
Data Connector runs within a private subnet, connects to the database and polls for new queries. There is no requirement to open traffic to the database or share credentials / connection strings.
Data Connector is built using another project we are working on Inferable (also open source) which is a runtime for building and observing LLM-based agents.
Would love your thoughts!
[1] https://arxiv.org/abs/2210.03629
[2] We have been testing these with various schemas and are currently working on better handling for large OpenAPI specs, etc."},"title":{"matchLevel":"none","matchedWords":[],"value":"Show HN: Data Connector \u2013 Chat with Your Database and APIs"},"url":{"fullyHighlighted":false,"matchLevel":"full","matchedWords":["ineffable"],"value":"https://github.com/inferablehq/inferable/tree/main/data-connector"}},"_tags":["story","author_johnjcsmith","story_42333823","show_hn"],"author":"johnjcsmith","created_at":"2024-12-05T23:00:20Z","created_at_i":1733439620,"num_comments":0,"objectID":"42333823","points":17,"story_id":42333823,"story_text":"Hey HN!
Wanted to share a project I have been working. Data Connector is an open source tool for interacting with Databases (Postgres, MySQL, SQLite) using natural language. Prompts are handled using a ReAct[1] agent which has access to the schema and a tool for executing queries.
It also has experimental[2] support for calling APIs (OpenAPI, GraphQL) which allows for queries that can span multiple systems (Find this user's details in Clerk, etc).
We have mostly been using it for managing our local development environment, but it has configurable controls for running in other environments.
- Privacy Mode which never sends query results back to the LLM context, instead the result is returned to the user as JSON
- Approval Mode which requires manual approval of each query before it is executed
Data Connector runs within a private subnet, connects to the database and polls for new queries. There is no requirement to open traffic to the database or share credentials / connection strings.
Data Connector is built using another project we are working on Inferable (also open source) which is a runtime for building and observing LLM-based agents.
Would love your thoughts!
[1] https://arxiv.org/abs/2210.03629
[2] We have been testing these with various schemas and are currently working on better handling for large OpenAPI specs, etc.","title":"Show HN: Data Connector \u2013 Chat with Your Database and APIs","updated_at":"2024-12-07T21:52:28Z","url":"https://github.com/inferablehq/inferable/tree/main/data-connector"},{"_highlightResult":{"author":{"matchLevel":"none","matchedWords":[],"value":"lunarcave"},"story_text":{"fullyHighlighted":false,"matchLevel":"full","matchedWords":["ineffable"],"value":"Hey HN!
We built Inferable to tackle some common challenges when putting AI systems into production. It's an open-source platform with a managed control plane to help simplify the development of reliable AI applications.
After working on several LLM-based projects, we kept running into the same issues:
- Workflows crashing and losing state\n- No good way to pause execution for human approvals\n- Need to build the same boilerplate for human approvals\n- Difficulty managing the lifecycle of long-running processes\n- Can't get structured output out reliably from every LLM\n- Repeated effort building infrastructure for structured outputs
We built Inferable to address these with:
- Persistent workflow state that survives crashes and restarts\n- Built-in human-in-the-loop functionality for approvals\n- A distributed architecture that separates orchestration from execution\n- Standardized methods for extracting structured data from LLMs
Your code runs in your infrastructure while our control plane handles the orchestration. If you're familiar with temporal, think of it as temporal with higher-level LLM-native primitives.
Everything is open-source (MIT license), and self-hosting options are available if you prefer to run it all yourself.
Would appreciate feedback from anyone building AI applications with similar challenges!"},"title":{"matchLevel":"none","matchedWords":[],"value":"Show HN: A managed platform to make building with LLMs easier"},"url":{"fullyHighlighted":false,"matchLevel":"full","matchedWords":["ineffable"],"value":"https://www.inferable.ai/"}},"_tags":["story","author_lunarcave","story_43279192","show_hn"],"author":"lunarcave","created_at":"2025-03-06T11:58:10Z","created_at_i":1741262290,"num_comments":0,"objectID":"43279192","points":1,"story_id":43279192,"story_text":"Hey HN!
We built Inferable to tackle some common challenges when putting AI systems into production. It's an open-source platform with a managed control plane to help simplify the development of reliable AI applications.
After working on several LLM-based projects, we kept running into the same issues:
- Workflows crashing and losing state\n- No good way to pause execution for human approvals\n- Need to build the same boilerplate for human approvals\n- Difficulty managing the lifecycle of long-running processes\n- Can't get structured output out reliably from every LLM\n- Repeated effort building infrastructure for structured outputs
We built Inferable to address these with:
- Persistent workflow state that survives crashes and restarts\n- Built-in human-in-the-loop functionality for approvals\n- A distributed architecture that separates orchestration from execution\n- Standardized methods for extracting structured data from LLMs
Your code runs in your infrastructure while our control plane handles the orchestration. If you're familiar with temporal, think of it as temporal with higher-level LLM-native primitives.
Everything is open-source (MIT license), and self-hosting options are available if you prefer to run it all yourself.
Would appreciate feedback from anyone building AI applications with similar challenges!","title":"Show HN: A managed platform to make building with LLMs easier","updated_at":"2025-03-06T12:02:51Z","url":"https://www.inferable.ai/"},{"_highlightResult":{"author":{"matchLevel":"none","matchedWords":[],"value":"lunarcave"},"title":{"matchLevel":"none","matchedWords":[],"value":"Back to basics: Why we chose long-polling over websockets"},"url":{"fullyHighlighted":false,"matchLevel":"full","matchedWords":["ineffable"],"value":"https://www.inferable.ai/blog/posts/postgres-nodejs-longpolling.mdx"}},"_tags":["story","author_lunarcave","story_42600276"],"author":"lunarcave","children":[42600494,42600993,42601110,42601287,42601348,42601351,42601370,42601428,42601467,42601495,42601705,42601817,42601878,42601957,42602310,42602977,42603205,42603226,42603734,42603986,42604157,42604247,42604272,42604445,42604507,42604576,42604585,42604974,42609109],"created_at":"2025-01-05T07:14:30Z","created_at_i":1736061270,"num_comments":163,"objectID":"42600276","points":258,"story_id":42600276,"title":"Back to basics: Why we chose long-polling over websockets","updated_at":"2026-02-18T07:06:12Z","url":"https://www.inferable.ai/blog/posts/postgres-nodejs-longpolling.mdx"},{"_highlightResult":{"author":{"matchLevel":"none","matchedWords":[],"value":"interpol_p"},"title":{"matchLevel":"none","matchedWords":[],"value":"Conversational AI agents for internal operations"},"url":{"fullyHighlighted":false,"matchLevel":"full","matchedWords":["ineffable"],"value":"https://www.inferable.ai"}},"_tags":["story","author_interpol_p","story_42802551"],"author":"interpol_p","children":[42804253],"created_at":"2025-01-23T10:10:26Z","created_at_i":1737627026,"num_comments":1,"objectID":"42802551","points":1,"story_id":42802551,"title":"Conversational AI agents for internal operations","updated_at":"2025-01-23T14:19:31Z","url":"https://www.inferable.ai"}],"hitsPerPage":50,"nbHits":27,"nbPages":1,"page":0,"params":"query=Ineffable&tags=story&hitsPerPage=50&advancedSyntax=true&analyticsTags=backend","processingTimeMS":7,"processingTimingsMS":{"_request":{"roundTrip":16},"fetch":{"query":5,"total":6},"total":7},"query":"Ineffable","serverTimeMS":9}