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You've got users, you've got bugs, you've got feature request so what the fuck do you build next?
Who's gonna tell human software engineers about...
Who's gonna tell vibe coders about...
1. SQL Injection
2. XSS
3. CSRF
4. CORS
5. SSRF
6. IDOR
7. Path Traversal
8. Mass Assignment
9. Clickjacking
10. Content Security Policy
11. Security Headers
12. Input Validation
13. Server-Side Authorization
14. Row-Level Security
15. Least Privilege
16. RBAC
17. Secrets Management
18. .env in .gitignore
19. API Key Rotation
20. Secret Scanning
21. Hashing vs Encryption
22. Password Salting
23. bcrypt & Argon2
24. JWT Expiry
25. Refresh Tokens
26. OAuth 2.0
27. OpenID Connect
28. Session Fixation
29. MFA
30. Brute Force Protection
31. Account Enumeration
32. Timing Attacks
33. File Upload Validation
34. Webhook Signature Verification
35. TLS Certificate Expiry
36. HSTS
37. Encryption at Rest
38. Dependency Vulnerabilities
39. Supply Chain Attacks
40. Threat Modeling
41. Indexes
42. EXPLAIN ANALYZE
43. N+1 Queries
44. Full Table Scans
45. Connection Pooling
46. Database Migrations
47. Down Migrations
48. Transactions
49. ACID
50. Isolation Levels
51. Deadlocks
52. Optimistic Locking
53. Pessimistic Locking
54. Normalization
55. Denormalization
56. Foreign Keys
57. Unique Constraints
58. Cascading Deletes
59. Soft Deletes
60. UUIDs vs Auto-Increment
61. Cursor-Based Pagination
62. Full-Text Search
63. Read Replicas
64. Replication Lag
65. Sharding
66. Partitioning
67. Hot Partitions
68. Postgres VACUUM
69. Materialized Views
70. Backups
71. Testing Your Restores
72. Point-in-Time Recovery
73. Change Data Capture
74. Outbox Pattern
75. ORM Lazy Loading
76. CAP Theorem
77. Eventual Consistency
78. Strong Consistency
79. Raft Consensus
80. Leader Election
81. Split Brain
82. Quorums
83. Clock Skew
84. Distributed Locks
85. Consistent Hashing
86. Bloom Filters
87. Two-Phase Commit
88. CQRS
89. Event Sourcing
90. Race Conditions
91. Backpressure
92. Load Shedding
93. Bulkheads
94. Jitter
95. Retry Storms
96. Cascading Failures
97. Thundering Herd
98. Cache Invalidation
99. Cache Hit Ratio
100. TTLs
101. Cache Warming
102. Write-Through vs Write-Back
103. Redis Eviction Policies
104. CDNs
105. Cache-Control Headers
106. ETags
107. Dead Letter Queues
108. Poison Messages
109. At-Least-Once Delivery
110. Exactly-Once Semantics
111. Message Ordering
112. Kafka Consumer Groups
113. Partition Keys
114. Background Jobs
115. Webhook Retries
116. DNS
117. DNS Propagation
118. HTTP Status Codes
119. HTTP Method Semantics
120. Keep-Alive
121. HTTP/2
122. WebSockets
123. Server-Sent Events
124. Long Polling
125. gRPC
126. Protocol Buffers
127. API Versioning
128. OpenAPI Specs
129. Backward Compatibility
130. Request Size Limits
131. Compression
132. Latency vs Throughput
133. Egress Fees
134. VPCs
135. Subnets
136. NAT Gateways
137. Firewalls
138. Security Groups
139. Service Mesh
140. Ingress Controllers
141. Health Checks
142. Liveness vs Readiness Probes
143. Graceful Shutdown
144. Connection Draining
145. Stateless Services
146. Failover
147. Multi-Region
148. Availability Zones
149. Single Points of Failure
150. Disaster Recovery
151. RTO & RPO
152. SLAs
153. SLOs
154. Error Budgets
155. Incident Response
156. On-Call
157. Runbooks
158. Postmortems
159. Chaos Engineering
160. Graceful Degradation
161. Autoscaling
162. Horizontal vs Vertical Scaling
163. Cold Starts
164. Capacity Planning
165. Load Testing
166. Memory Leaks
167. OOM Killer
168. Structured Logging
169. Log Levels
170. Log Rotation
171. Distributed Tracing
172. OpenTelemetry
173. Correlation IDs
174. Metrics Cardinality
175. p99 Latency
176. Alert Fatigue
177. Error Tracking
178. Profiling
179. Flame Graphs
180. Infrastructure as Code
181. Terraform State
182. GitOps
183. Blue-Green Deployments
184. Canary Releases
185. Rollbacks
186. Feature Flags
187. Environment Parity
188. Staging Environments
189. 12-Factor Apps
190. Multi-Stage Builds
191. Non-Root Containers
192. Image Scanning
193. Resource Requests & Limits
194. Pod Disruption Budgets
195. Semantic Versioning
196. Lockfiles
197. Reproducible Builds
198. Branch Protection
there is generational wealth waiting for the person who figures out how to teach a mid employee to use AI without becoming stupid.
if software is mostly a solved problem...what happens next?
Figure out what you really like doing or you're gonna get beaten by someone using AI who really, really loves the problem you're half-heartedly trying to solve.
If building software is a solved problem, what's next?
nicharalambous.com/blog/buil…
This is a sad advert.
Meta's premise is that everyone must record live events and therefore Meta "creep" Glasses are optimal.
What if, and hear me out before you hate on me, but what if people stopped recording and just enjoyed the tennis?
Let's go back to the 1400s when nobody had multiple priorities (because the word didn't exist)...
In your team at work, at home, with your family, in your side business...
One priority to rule them all and the other ones to bind them.
We can't be everywhere at once and if you're focused on everything then you're focused on nothing. If everything is urgent, nothing is urgent.
This is one of the reasons I'm happy paying taxes in the Netherlands. Public transport just works and is affordable.
When I can use my tax money every day, it changes how I feel about paying.
Three months ago people said this about chatgpt and in 6 months from now they'll say it about Grok or Gemini or Claude or GPT again.
Tough to tool-chase. I try to force Claude to follow instructions around how to answer me nut its not always perfect.
I find it mroe disruptive to keep switching.
I absolutely hate the way Claude (Fable and Opus) writes - it’s so full of itself, so fake-eloquent without saying anything, so know-it-all, presenting the simplest insights in a repulsively smug tone - and it seems impossible to get rid of all these Claude-isms it produces even with strict global instructions.
Can’t stand any more “load-bearing assumptions”, any sentences that end with “and that’s the one point that lands with me”, generally any short sentences that start with “And” and a complete over-use of references to “the one XYZ”.
It feels like AI for people who have never learned how to communicate succinctly, and who constantly have the need to feel smarter than everyone around them (hint: they’re not smarter, they’re just insecure).
ChatGPT, Grok and Kimi are miles ahead on producing a more natural communication style. The actual analysis, the automations and the artifacts might (often) be better - but Claude just feels so repulsively unlikeable to interact with.
If you target everyone, you target no one when you start a business.
HYPER focus is the key to growing your side business -- or any business tbh.
Get specific, the more detailed the better.
It feels confusing that I have to pay to maintain ExpoGo on @Replit when Replit forces me to use it to test my apps.
Every successful business I've built started out small and then grew big.
It's impossible to imagine building a huge business before you figure out what you're building, who you're it's for & why you're building it.
These are the only 4 anchors you need to start.
Nothing tells the world that American companies develop tech responsibly.
The world deserves confidence that American companies developing increasingly capable AI will act responsibly, especially as the trajectory of progress has steepened. Every frontier lab must deliver on this, and there is no reason any of us should come to work if we cannot.
We welcome a federal framework that sets consistent safety requirements for frontier AI. But we do not believe we need to wait for an anti-trust exemption or legislation to begin the work of providing this confidence. Consistent rules to manage frontier risk so that we can maximize the benefits are a good idea (and we are excited by ideas like independent auditors).
Years ago, companies like ours developed things like Responsible Scaling Policies and Preparedness Frameworks. Those were good for that moment, and focused primarily on the deployment of completed models, not what happens during their development process.
Today's shift to focusing on safe development and evaluation will need new tools. For example, at OpenAI we now formulate explicit safety cases in advance of frontier reinforcement learning runs we expect to significantly increase capability, in addition to the safety work we have long done in advance of model releases.
We hope that other companies will learn from our approaches and propose their own; we think shared standards for misalignment, monitoring, and safety will lead to better outcomes. We look forward to collaborating with our colleagues across the industry to formulate the best version of these.
When we talk about “pacing”, we do not mean “stopping”. Progress has been rapid and will continue to be. But it should be slower than it otherwise could be; interventions like safety cases and monitoring have significant costs.
Pacing will be well worth this cost; no amount of American competitive pressure should justify recklessness, or let capabilities get ahead of alignment and monitoring.
Where we will need the help of our government is for international coordination. But first we should do what we can ourselves.
It doesn't matter if everything has been built. You're not competing with everything to build a business.
What's your definition of success for this idea? $1000 per month? Great. 100 people paying $10 pm is all you need.
That's 100 ppl in the entire world who've never used or heard of your competitors.
Build. Ship. Tell people about it and repeat until you get there.













