The part about AI helping to build up tacit knowledge much more rapidly than before doesn't sound right to me though.
I guess it could definitely be used to capture/document tacit knowledge that already exists.
But for knowledge that doesn't exist yet, even if an AI were to suggest a million different experiments, the bottleneck here will be running all those experiments, waiting for the results and making changes accordingly. This loop would inevitable be slow and could even span decades (if that was how long it took to build the tacit knowledge in the first place).
How exactly do you handle hallucinations? Hallucinations need not just be in the citations, right? And what if there are hallucinations without any citations?
You need to step back from the day-to-day and see if you are able to generate any meaningful accomplishments at the end of a month or a quarter. Things being a little random at a day level is okay if you are ultimately growing as an IC with projects / accomplishments that can help you for your next job or promotion.
People who are in constant PoC mode will eventually get burnt out and won’t get rewarded for it either. It’s a sign of poor management. See if you can work with your manager to create a set of quarterly goals to accomplish which are meaningful to the organisation. Unless your org is a very early stage startup, they should be able to do this. If not, time to find a new job or you’ll end up having wasted your time
I head engineering for an enterprise SaaS startup in the manufacturing space. Wanted to add a few points to this:
1. Software Integrations: Enterprise software is almost never deployed in a vacuum. There will be a ton of existing software that companies use that they would want you to integrate with - most commonly being either some CRM like Salesforce or an ERP like SAP, Oracle. When pitching to a customer, it would be great to try and learn what existing software tools they use and see if opportunities exist to try and integrate with them ultimately. This will make your software very very hard for them to get rid off later and will also help distinguish you from your competitors who might try to be avoiding integrations. Designing your architecture with integrations in mind is a good idea.
2. Audit logs: Depending on the industry, there might be a strong requirement for compliance/auditing. The enterprise would want to ensure that every action undertaken on the platform is audited and can be reviewed on-demand later.
3. On-premise vs Cloud deployments: You might find certain clients that operate their own hardware and software and want you to just hand them some executable that they can deploy in their systems. On the other hand you'll also find companies that have gone all-in on cloud and won't bat an eyelid as long as you are deployed on some known cloud like Azure, AWS or GCP. Increasingly more and more companies are going the private cloud route and ask you to deploy on their cloud accounts (most commonly Azure - Microsoft has a much stronger hold on the enterprise market). Be prepared to handle requests like these. In several cases, you might be able push to have the SaaS being served from your cloud accounts but not always.
4. IT departments: Enterprise companies will invariably have an IT department that is supposed to ensure that the procurement process goes smoothly from a technical perspective and that you are compliant with all of their technical requirements. Their primary job is to ensure their asses are covered and nobody blames them later for technical/compliance issues later. Do not cut them out of the sales process. While they don't have the ability to approve the sale, they definitely have the ability to block it. Involve them closely and get their strong buy-in so that they don't become a bottleneck later.
Does this also support in-app notifications? If I wanted to show the last 20 notifications for each user inside my application, is there any API for getting those?
Hi ! I am interested! Would be a great opportunity to learn something new while delivering real value to the world! My personal email is in my HN profile!
The part about AI helping to build up tacit knowledge much more rapidly than before doesn't sound right to me though.
I guess it could definitely be used to capture/document tacit knowledge that already exists.
But for knowledge that doesn't exist yet, even if an AI were to suggest a million different experiments, the bottleneck here will be running all those experiments, waiting for the results and making changes accordingly. This loop would inevitable be slow and could even span decades (if that was how long it took to build the tacit knowledge in the first place).